Job Board

• Join us as Senior Computer Vision Expert (f/m/d) at our Smart Products and Advanced Technologies (SPA) department - the R&D Competence Center for the Siemens Mobility GmbH. We do have the mission to innovate technologies in the fields of digitalization, automation, and electrification in the Mobility domain.
• You will apply your hands on skills, but also guiding our technical team of 20 and more team members.
• In your new role you will push forward our activities in the field of autonomous driving in the rail domain.
• You will technically drive the calibration of complex sensor setups and create new concepts for self-calibration techniques.
• In addition, you will be responsible to define and setup technical roadmaps in computer vision.
• With your knowledge you support the execution of customer projects, but also the definition of new R&D topics.
• Last but not least: Enthusiasm to build a product that doesn’t yet exist – nowhere in the world!

• You hold a completed PhD degree in robotics, information technology or physics.
• Deep know-how in 2D/3D Computer Vision, Machine Learning, Optimization and multiple view geometry is mandatory.
• You bring in long-term experience in software development within an industrial context combined with knowledge in how solutions can be deployed into the field successfully.
• In addition, practical know-how for sensors such as camera & Lidar & GNSS, embedded computing platforms is required.
• Furthermore, you are experienced in coding C/C++ and python in a team and you have used libraries like OpenCV, dlib and pytorch.
• You have worked with 3D point clouds and real time operating systems, and have successfully calibrated sensor setups.
• You are fluent in English. German language skills are nice to have.

At Compass, we envision a world where the experience of selling or buying a home is simple and pleasant for everyone. Founded in 2012, Compass provides an end-to-end platform that empowers residential real estate agents to deliver exceptional service to their seller and buyer clients, all in service of our mission to help everyone find their place in the world.

About The Team

The Compass Computer Vision (Video and RE/COgnition) team makes it easy for customers to add text, image and video analysis to real estate applications with no machine learning expertise required. With Compass Computer Vision, you can enrich listing descriptions, tag rooms and listings, identify objects and scenes in text, image and video providing immersive virtual tour experiences from physical or creative data sources.

Our team's goal is to disruptively improve customers' experience and business by creating a text, image and video-analysis platform for real estate applications. This includes:

Developing text, image and video-analysis solutions for agents to leverage to grow their business. Agents and their clients can easily understand the problems we are solving, and will share our conviction that these solutions will help them win and serve more clients.
Embracing radical simplicity. We strive to deliver very simple user experiences that enable agents to adopt with as little effort as possible. We also prefer simple and scalable solutions to complex ones.
Not reinventing the wheel. We take pains to benchmark and understand state of the art open source and cloud AI solutions. We use this learning to achieve speed and quality in our work, and leverage existing tools when it makes sense to #MoveFast on behalf of our customers.
Doing rapid prototyping to test ideas with customers. We believe that low cost mockups, hackathons and quick prototypes are invaluable for learning what works. We are not afraid of failed prototypes or ideas that didn’t work when tested with customers, because we believe that even a few amazing wins from our process of rapid iteration will more than compensate for early failures.
Building APIs that are productized, platformized and reusable. We build and own well-designed APIs that can be easily integrated by many Compass applications, and follow the best practices of API design, documentation and support.

About The Role

As a Senior Machine Learning Scientist on the Computer Vision team, you will work closely with engineers, designers, and product managers to invent software prototypes for image classification, object detection, video understanding, rendering, 3D reconstruction technologies in the real estate industry. You will have the opportunity to help create, build, deploy and test novel image classification, object detection, video understanding, 3D reconstruction, image to caption systems and algorithms. You will have an impact on shipping applications with millions of users and help define this new effort from the start. You will also have an opportunity to create/lead image classification, object detection, video understanding, rendering, and 3D reconstruction projects

At Compass You Will:

Build, develop and deploy performant and scalable image processing/enhancement, video stitching services
Build, develop and deploy image classification, object detection, video understanding, 3D reconstruction, image to caption services
Collaborate with product managers and work with an engineering-focused, iterative team to build and establish product requirements
Quickly prototype new demos and systems for real estate image and video understanding
Quickly prototype new demos and systems for image classification, object detection, video understanding, rendering, 3D reconstruction, image to caption
Build systems on top of state-of-the-art CV algorithms across Compass’ platforms, as well as third-party services
Iterate and prototype rapidly

What We Look For:

MS in Computer Vision, Computer Graphics, or Computer Science.
5+ years of relevant experience
Must possess a strong background in Computer Vision or Computer Graphics
Experience with machine learning algorithms such as CNN, Resnet, Pytorch, Tensorflow, etc.
Experience in optimization on GPU / CPU / other architectures (CUDA, SSE, NEON, OpenMP or other SIMD)
Experience with deep learning / object reconstruction / registration / classification / recognition / rendering
Testing, documentation, and verification of or image classification, object detection, video understanding, rendering, 3D reconstruction, image to caption
Experience with Agile methods, Scrum / Kanban / etc.
Knowledge of scripting language, e.g. Python, Bash, etc.
Camera and/or image/or graphics/or video pipeline knowledge and experience

Nice to Have:

Ph.D. in Computer Vision, Computer Graphics, or Computer Science.
Prior experience involving image processing, computer graphics, video processing, geometrical computer vision is a big plus.
Prior experience involving image classification, object detection, video understanding, rendering, 3D reconstruction, image to caption is a big plus.
Experience with existing computer vision libraries such as OpenCV, PCL, CGAL, Eigen, etc.

Applications are invited for a funded PhD position in deep learning for visual recognition applications. The candidate will work under the supervision of Prof. Granger at the Laboratory of imaging, vision and artificial intelligence (LIVIA), Dept. of Systems Engineering, ETS Montreal. This fully-funded position is available immediately, for a duration of 4 years, and offers a competitive salary exempt of taxes. It also offers a possibility for collaborations-internships with top R&D companies and institutions in Montreal and abroad.

We are looking for a highly motivated doctoral student who is interested in performing cutting-edge research on machine learning models applied to visual object recognition, with a particular focus on deep learning architectures (e.g, auto-encoders, convolutional and recurrent neural networks), domain adaptation, multimodal and spatiotemporal fusion, and weakly-supervised learning. Application areas include expression recognition in health monitoring, medical image analysis, and person re-identification in video surveillance.

Prospective applicants should have the following profile:
• strong academic record with an excellent M.Sc. degree in computer science, applied mathematics, or electrical engineering, preferably with expertise in one or more of the following areas: machine learning, computer vision, pattern recognition, artificial intelligence;
• good mathematical background;
• Excellent written and verbal communication skills in English;
• good programming skills in languages such as C, C++, and Python, with knowledge of deep learning frameworks (e.g., Pytorch);
• publication in one of the major conferences or journals in computer vision and machine learning would be an asset.

Application process:
For consideration, please send your CV, names and contact details of two references, transcripts, a link to a M.Sc. thesis, as well as relevant publications to: eric.granger@etsmtl.ca

Open position: The Department of Radiology at Boston Children’s Hospital and Harvard Medical School invite applicants for a full-time position at the postdoctoral research fellow level.

Topic: The funded project involves developing and using medical image analysis and deep learning algorithms to quantify normal brain development and to detect early signs of abnormalities in brain magnetic resonance images (MRIs).

Candidate qualifications: The successful candidate will be in the final year of PhD or have a PhD degree in the Data Science, Biomedical Enginering, Computer Science/Engineering, Applied Maths, Computational Neuroscience, or related fields. Experience in machine learning and medical image analysis is preferred.

Timeframe: The starting date can be as early as June 1st, 2021. The position will be open until filled. The period is 2 years given satisfactory progress evaluated at the end of the first year. Continuous stay beyond 2 years is possible based on performance and funding, and we will encourage and help the fellow to apply for his/her own funding for further career development.

Team: The new member will be working closely with
- P. Ellen Grant, MD, Professor of Radiology at Harvard Medical School, specializing in neuroradiology, neuroscience, and pediatric neurodevelopmental, Founding Director of the Fetal-Neonatal Neuroimaging Developmental Science Center (FNNDSC, https://www.fnndsc.org) that has ~10 faculty, ~10 postdoc fellows, and ~20 research scientists or assistants, and
- Yangming Ou, PhD, Assistant Professor of Radiology working on medical image analysis and machine learning, faculty member of FNNDSC, and Director of affiliated Image, Informatics, and Intelligence (I3) Lab (https://projects.iq.harvard.edu/i3-lab).
Members of the team (postdoc fellows, PhD students, and research assistants) work on MRI analysis and machine learning for abnormality detection, early screening of disorders, outcome prediction, treatment evaluation, and neuroimaging biomarkers for typical and atypical brain development in children and beyond.

To apply: Please send your CV to Dr. Yangming Ou at yangming.ou@childrens.harvard.edu.

Disclaimer: Boston Children’s Hospital and Harvard Medical School is an equal employer. Applications will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, gender identity, sexual orientation, pregnancy, and pregnancy-related conditions or any other characteristic protected by law. Under-represented groups in STEM are especially encouraged to apply.

We are looking for a production-oriented, computer vision engineer to design, develop and implement computer vision and machine learning cutting-edge technologies to ensure our market-leading position in sports player tracking and broadcast solutions.

Design, prototype, implement and test software and computer vision & machine learning algorithms in Python and C++.
Develop and optimize real-time and high-accuracy sports solutions with modern CV: object detection, recognition and tracking, camera calibration, 3D reconstruction, etc.
Leverage Amazon Web Services (EC2 and S3) to run algorithms on a large number of servers in the cloud.
Implement and provide best-practices for maintainable software development, including deployment process, documentation, and adherence to and improvement of coding standards.
Support and monitor live systems, including on-call rotation for computer vision systems during sports seasons.
Manage interdisciplinary projects in collaboration with different groups within the company.
Continuously learn new applications and apply learnings to new challenges.

The Future Forward Research group within Intuitive Surgical has an immediate opening in Sunnyvale, CA for a research engineer with focus on Computer Vision, Machine Learning and Software development, contributing to new technology development in the area of 3D scene understanding/reconstruction and spatial AI systems for next generation robotic surgery platforms. This role is an exciting opportunity to join a newly formed team and contribute to its future growth and it will give you an opportunity to test your knowledge in a challenging problem solving environment.

The successful candidate must excel in a high-energy, focused, small-team environment, and have a commitment to high quality research prototypes and concepts. A strong sense of shared responsibility and shared reward is required.

As part of the research team, immediate responsibilities include:

• Contribute to research projects that develop a variety of algorithms and systems in computer vision and machine learning.
• Participate in integration of new ML/CV algorithms into existing and future robotic platforms
• Participate in development of prototype 3D recognition systems that scale to large clinical datasets
• Participate in development of prototype dense 3D reconstruction systems based on multi-view image sensors
• Optimize deep neural networks and the associated preprocessing/postprocessing code to run efficiently on an embedded device
• Train machine learning and deep learning models on a computing cluster to perform visual recognition tasks, such as segmentation and detection
• Contribute to building new clinical datasets and data pipelines
• Develop new technologies and digital products to improve surgeon and team performance on robotic surgery platforms.
• Support academic collaborations in related fields.

Additional responsibilities include:
• Contribute to multiple areas of research, including but not limited to the following:
o Design and apply CV/ML algorithms to novel, surgical applications
o Design/bring-up of novel sensing technologies
o Characterize surgeon and team behavior and workflow to optimize new technologies
• Establish strong academic collaborations across research disciplines

The Future Forward Research group within Intuitive Surgical has an immediate opening in Sunnyvale, CA or Aubonne Switzerland for a research scientist with focus on Computer Vision, Deep Learning and Image Analytics, contributing to new technology development in the area of 3D scene understanding/reconstruction and spatial AI systems for next-generation robot-assisted surgery platforms. This role is an exciting opportunity to join a newly formed team and contribute to its growth and it will give you an opportunity to test your knowledge in a challenging problem solving environment.

The successful candidate must excel in a high-energy, focused, small-team environment, be able to initiate and drive new research directions, and have a commitment to high research quality. A strong sense of shared responsibility and shared reward is required.

As part of the research team, immediate responsibilities include:

• Research, design and implement algorithms in deep learning for computer vision and image analytics
• Contribute to research projects that develop a variety of algorithms and systems in computer vision, image and video analysis.
• Advance the state-of-the-art in the field, including generating patents and publications
• Develop prototypes of 3D recognition models that scale to large clinical datasets
• Develop prototypes of dense 3D reconstruction systems based on multi-view image sensors
• Contribute to building new clinical datasets and data pipelines
• Participate in integration of new ML/CV algorithms into existing and future robotic platforms
• Experiment with several users and clinical advisors to iterate prototype designs based on feedback and performance.
• Develop new technologies and digital products to improve surgeon and team performance on robotic surgery platforms.
• Support academic collaborations in related fields.

Additional responsibilities include:
• Contribute to multiple areas of research, including but not limited to the following:
o Design and apply CV/ML algorithms to novel, surgical applications
o Design/bring-up of novel sensing technologies
o Characterize surgeon and team behavior and workflow to optimize new technologies
• Establish strong academic collaborations across research disciplines

dBRAIN is an interdisciplinary initiative within the ‘Digital Futures’ initiative at KTH Royal Institute of Technology, Stockholm (https://www.digitalfutures.kth.se/research/collaborative-projects). The goal is to better understand neurodegenerative diseases such as Parkinson’s disease and Alzheimer’s disease. We combine computational modeling, machine learning and topological data analysis to identify causal links among disease biomarkers and disease symptoms. This understanding should improve diagnosis, prediction of the disease progres- sion and suggest better therapies. We are now looking for up to five postdocs. Each selected candidate will work in close collaboration with other PIs in the dBrain consortium, including researchers and clinicians at Karolinska Institute and Karolinska Hospital.

Two of the positions deal with medical imaging and medical image processing: one in image processing of high-dimensional brain imaging data, and one in magnetic resonance elastography in the brain.

Medical imaging modalities such as Magnetic Resonance Imaging (MRI) often produce high-dimensional image data in vector or tensor format, e.g. diffusion tensor MRI or functional MRI. For the computationally demanding post-processing of such data, we use modern machine learning techniques like convolutional neural networks, graph convolutional networks and reinforcement learning. This project will deal with developing, adapting and applying such techniques to imaging data from patients with neurodegenerative diseases, available to us thanks to our close cooperation with Karolinska Institute.

The workplace will be the Department of Biomedical Engineering and Health Systems, located in Huddinge in Southern Stockholm, next door to Karolinska university hospital Huddinge, a cross-disciplinary research environment focusing equally on engineering excellence and clinical usability.

Deadline for application: 30 April, 2021. Applications can only be made via the link below.

SRI International creates world-changing solutions to make people safer, healthier, and more productive. SRI’s Center for Vision Technologies (CVT) offers end-to-end vision solutions that translate into real-world applications. We pride ourselves in pushing the frontiers of R&D in Video and Vision Technologies with the goal of “making Vision work in the real world”. If you dream of making robots see and navigate, search the Web’s pictures and videos, train and educate people with augmented reality, understand “who, what, where and how” through Vision, and have the skills and aptitude to work on challenging problems, SRI may be the place for you. We work on a wide range of projects, from basic research to applied research for government and commercial applications.

CVT has a variety of technical staff positions currently open for different areas in Computer Vision, Robotics, AI and Machine Learning including:

Computational Sensing and Neuromorphic Computing
•Multi-sensor fusion and Smart sensing
•Neuromorphic processing and Embedded low power machine learning

2D/3D reasoning
•Navigation and semantic 3D mapping and modeling
•Surveillance

Collaborative Autonomy
•AI based control
•Centralized and De-Centralized Planning of Heterogenous Swarms

Human behavior modeling and Human Computer Interaction
•Augmented reality
•Human State Monitoring and Emotion estimation
•Communicating with Computers

Multi-modal data analytics
•Activity understanding
•Image search. Fine grain recognition & Visual question answering
•Social media reasoning

Machine Learning
•Explainable and Robust AI
•Life Long Learning and handling surprise
•Learning with less labels

To apply please go to www.sri.com/careers and search key word: vision, or you can email a resume to erica.saunders@sri.com.

Closing Date: 30th, April 2021

We look for a highly motivated pre- or post-doctoral researcher to conduct cutting-edge research in machine learning for forensic anthropology. In particular, this 2-year research contract will be focused on forensic facial comparison, with possible extensions to biological profile estimation and forensic identification by means of comparative radiography or craniofacial superimposition. The work will be mainly focused on the design, analysis and implementation of machine learning, deep learning and computer vision algorithms in the forensic medicine domain, with special emphasis on the development and application of explainable AI techniques.

We will only consider excellent candidates having PhDs or MScs in computer science or a research field with an interdisciplinary background in some of the following areas: machine learning, deep learning, pattern recognition, computer vision, biomedical image analysis, computational intelligence/soft computing. They should have a proven record in research, innovative thinking, real-world problem solving and fast prototyping.

The selected candidate will work at the Department of Computer Science and Artificial Intelligence (DECSAI) of the University of Granada (UGR), one of the top institutions in computer science and engineering (ranked 1st in Spain according to the Academic Ranking of World Universities 2020).

Qualified applicants are requested to send their documents (motivation letter, résumé, and list of publications) as a PDF file (in English or Spanish) by e-mail to pmesejo@ugr.es.

Closing Date: 30th, April 2021

We look for a highly motivated pre- or post-doctoral researcher to conduct cutting-edge research in machine learning for forensic anthropology. In particular, this 2-year research contract will be focused on forensic facial comparison, with possible extensions to biological profile estimation and forensic identification by means of comparative radiography or craniofacial superimposition. The work will be mainly focused on the design, analysis and implementation of machine learning, deep learning and computer vision algorithms in the forensic medicine domain, with special emphasis on the development and application of explainable AI techniques.

We will only consider excellent candidates having PhDs or MScs in computer science or a research field with an interdisciplinary background in some of the following areas: machine learning, deep learning, pattern recognition, computer vision, biomedical image analysis, computational intelligence/soft computing. They should have a proven record in research, innovative thinking, real-world problem solving and fast prototyping.

The selected candidate will work at the Department of Computer Science and Artificial Intelligence (DECSAI) of the University of Granada (UGR), one of the top institutions in computer science and engineering (ranked 1st in Spain according to the Academic Ranking of World Universities 2020).

Qualified applicants are requested to send their documents (motivation letter, résumé, and list of publications) as a PDF file (in English or Spanish) by e-mail to pmesejo@ugr.es.

Amazon Go/Dash Cart in Boston's Metro-West

Amazon Dash cart allows shoppers to checkout without lines — you just place the items in the cart and the cart will take care of the rest. When you’re done shopping, you leave the store through a designated dash lane. We charge the payment method in your Amazon account as you walk through the dash lane and send you a receipt. Check it out at https://www.amazon.com/b?ie=UTF8&node=21289116011.
Designed and custom-built by Amazonians, our Dash cart uses a variety of technologies including computer vision, sensor fusion, and advanced machine learning. Innovation is part of our DNA! Our goal is to be Earth’s most customer centric company and we are just getting started. We need people who want to join an ambitious program that continues to push the state of the art in computer vision, machine learning and algorithms.

As an applied scientist, you will help solve a variety of technical challenges and mentor other engineers. You will play an active role in translating business and functional requirements into concrete deliverables and build quick prototypes or proofs of concept in partnership with other technology leaders within the team. You will tackle challenging, novel situations every day and given the size of this initiative, you’ll have the opportunity to work with multiple technical teams at Amazon in different locations. You should be comfortable with a degree of ambiguity that’s higher than most projects and relish the idea of solving problems that, frankly, haven’t been solved before - anywhere. Along the way, we guarantee that you’ll learn a ton, have fun and make a positive impact on millions of people.

BASIC QUALIFICATIONS
Position Requirements

Master’s or PhD degree or foreign equivalent in Computer Science, Machine Learning, Statistics, or a related field and one year of research or work experience in the job offered, or as a Research Scientist, Research Assistant, Software Engineer, or a related occupation. Minimum five years of research or work experience in a related occupation and broad research experience after PhD degree or equivalent. Must have five year of research or work experience in the following skill(s): programming with C, C++, or Python; utilizing computer vision and machine learning technologies (deep learning or related); and analyzing and developing vision-based systems for complex project projects in Artificial Intelligence.
PREFERRED QUALIFICATIONS

· PhD in computer vision, machine learning, or related discipline
· Depth and breadth in state-of-the-art computer vision and machine learning technologies
· Publications at top-tier peer-reviewed conferences or journals
· Proven track record of innovation in creating novel algorithms and advancing the state of the art
· Ability to develop practical solutions to complex problems
· Strong communication and collaboration skills
· Proficiency in C/C++ and/or python

Please apply here: https://www.amazon.jobs/en/jobs/1503850/sr-applied-scientist-iii?no_int…

Amazon Prime Air develops autonomous drones that are able to deliver packages to customers' backyards in 30 minutes or less. To achieve this, our team needs to push the state of the art in computer vision and machine learning. We are looking for motivated and highly skilled computer vision scientists to support our journey.

BASIC QUALIFICATIONS
· 4+ years experience in (applied) computer vision research
· Graduate from an accredited college or university
· PhD or MS degree in Computer Vision, Machine Learning or related field
· Experience with Deep Learning
· Proficient in C++ and Python coding skills

PREFERRED QUALIFICATIONS
· Experience building complex software/hardware mission-critical systems that have been successfully delivered to customers at scale
· Knowledge of engineering practices and patterns for the full software/hardware/networks development life cycle, including coding standards, code reviews, source control management, build processes and testing
· Strong verbal and written communication skills
· Experience communicating with various teams to collect requirements, describe product features and technical designs
· Strong publication record at major venues, such as, cvpr, iccv or eccv

The NIRAL Lab in the Department of Psychiatry, and Neuroscience Center at the University of North Carolina at Chapel Hill seeks a talented, highly motivated postdoctoral researcher with a background in machine learning and/or biomedical image processing. The NIRAL Lab is developing software to support AI-driven techniques to rapidly diagnose, track, and treat neurodisorders.

Responsibilities for this position include a combination of:

● Developing deep-learning approaches for insight and analysis about mouse behavior from video

● Machine Learning: use your expertise in statistics and machine learning to analyze high dimensional medical imaging data

● Make it easy to get high quality, automated, results without expert intervention. Build scalable products and reusable libraries in Python, Scala, and/or C++, taking advantage of Spark, Hadoop, and other tool stacks as appropriate.

● Developing computational and algorithmic approaches to understand the neurobiological mechanism of neurodisorders

● Interact cross-functionally: work with people across the team to find creative solutions and deliver them

● Skilled at data visualization and presentation The candidate will be called upon to present work at national and international research conferences.

Required Qualifications:

● Ph.D. in Computer Science, Information Science, Biomedical Data Science, Mathematics, Statistics, or a related technical discipline.

● Experience with Computer Vision and Deep Learning architectures (CNNs, RNNs, etc).

● Strong foundation in machine learning and data science.

● Programming skills with proficiency in Python, Java, and/or R.

Desired Qualifications:

● Experience with neuroimaging/neuroscience studies.

● Experience with machine learning frameworks such as scikit-learn, TensorFlow, PyTorch, and/or Keras.

● Experience with biomedical image processing

● Ability to present/visualize outputs to multidisciplinary audience.

Required Application Materials:

● Cover Letter

● Statement of Interest

● Curriculum Vitae

● Contact information from 3 references

Contact:

Guorong Wu, PhD

Assistant Professor, Department of Psychiatry

University of North Carolina at Chapel Hill

919.966.2216

grwu@med.unc.edu

The ACM Lab in the Department of Psychiatry, Computer Science, and Neuroscience Center at the University of North Carolina at Chapel Hill seeks a talented, highly motivated postdoctoral researcher with a background in biomedical image processing with the focus on image registration and shape analysis. The ACM Lab is developing computational tool to understand how genetic factors affect brain structure using tissue clearing and microscopic technologies.

Responsibilities for this position include a combination of:

● Developing image registration algorithm for large-scale microscopy images of mouse brain.

● Developing computational and algorithmic approaches to understand the brain development.

● Interact cross-functionally: work with people across the team to find creative solutions and deliver them

● Skilled at data visualization and presentation The candidate will be called upon to present work at national and international research conferences.

Required Qualifications:

● Ph.D. in Computer Science, Information Science, Biomedical Data Science, Mathematics, Statistics, or a related technical discipline.

● Experience with computer vision and medical imaging.

● Strong foundation in machine learning and data science.

● Programming skills with proficiency in Python, C/C++, and/or Matlab.

Desired Qualifications:

● Experience with neuroimaging/neuroscience studies.

● Experience with biomedical image processing

● Ability to present/visualize outputs to multidisciplinary audience.

Required Application Materials:

● Cover Letter

● Statement of Interest

● Curriculum Vitae

● Contact information from 3 references

Contact:

Guorong Wu, PhD

Assistant Professor, Department of Psychiatry

University of North Carolina at Chapel Hill

919.966.2216

grwu@med.unc.edu

Founded by Dr. Yuanqing LIN in November 2017, Aibee is a leading AI startup providing AI solutions, and its mission has been to empower and upgrade the vertical market with AI. We are a leading company in the application of AI technologies for the retail industry, have developed full AI solutions for offline retailers that enable them to close the loop among data, algorithms, and product/service. Aibee applies the most advanced and innovative AI technologies (computer vision, speech recognition, natural language understanding, big data analytics, robotics, etc.) and has become the strategic partner of many of the world’s largest retail chains.

We are expecting top-notch Computer Vision Algorithm Scientists to join our R&D center in Palo Alto (currently remote), work on production-level computer vision and deep learning models with a group of talented engineers/scientists. We have access to a huge amount of real retail data, enabling researchers like you to develop complex models and techniques at scale.

The problems range from various research domains in Computer Vision and Machine Learning such as:

• Activity Recognition and Event Detection
• (Multi-Camera) Multiple Target Tracking
• Re-identification and Metric Learning
• Holistic visual understanding
• Object Detection, Segmentation, and Classification
• Pose Estimation and Tracking

Preferred Qualifications:
• PhD (or master with at least 3 years working experience) in Computer Science, EE, Applied Mathematics, or related fields.
• Strong publication record in premier AI-related venues such as CVPR, ICCV, ECCV, NeurIPS, or other related major conferences or journals.
• Strong analytical and problem-solving skills.
• Team player with good communication skills.
• Strong coding skills with Python or C++.

Benefits:
• Comprehensive Medical, Dental and Vision Insurance
• Retirement Plan
• Generous PTO and Paid Holidays
• Daily Meal and Bi-weekly Happy Hours
• Flexible WFH Policy
• Frequent Tech Talks

SnT is a leading international research and innovation centre in secure, reliable and trustworthy ICT systems and services. We play an instrumental role in Luxembourg by fueling innovation through research partnerships with industry, boosting R&D investments leading to economic growth, and attracting highly qualified talent. We’re looking for people driven by excellence, excited about innovation, and looking to make a difference. If this sounds like you, you’ve come to the right place!

Your Role
The successful candidates will join the Computer Vision, Machine Intelligence and Imaging (CVI2) headed by Prof. Djamila Aouada in order to carry out research in the general area of Computer Vision. CVI2 is a young group composed of highly motivated and active members. Their work focuses on innovative research topics such as 3D shape modelling, 6DOF object pose estimation, human behavior understating, and deep learning and is disseminated in top-tiers venues. This is a fully funded Postdoc position for 2 years. The position holder will be involved in ESA funded projects and will be working closely with our industrial partner POST. He/she will be required to perform the following tasks:

• Propose and develop models and algorithms (Predictive models, Artificial Intelligence, Machine Learning, etc.) in order to meet the projects demands
• Work closely with project’s stakeholders
• Shaping research directions and producing results
• Attracting funding in cooperation with industrial partners
• Participating in proposal writing
• Coordinating research projects and delivering outputs
• Disseminating results through scientific publications
• Providing guidance to PhD and MSc students
• Participating to the teaching activities
• Providing support in setting up and running experiments in the SnT Computer Vision laboratory
• Proposing and implementing real-time solutions
• Participating in organizing relevant workshops and demonstrations

Your Profile
• A PhD degree in Electrical Engineering, Computer Science, Applied Mathematics or a related field
• Highly experienced in one or more of the following topics:
• Computer vision
• Pattern recognition
• Deep learning/machine learning
• Experience with European projects (FP7/H2020), national/international projects and/or industrial project
• Strong mathematical background
• Experience with machine learning algorithms
• Commitment, team working and a critical mind
• Strong development skills in Python, C and C++
• Familiarity with deep learning frameworks such as Pytorch and Tensorflow
• Fluent written and verbal communication skills in English are mandatory

Here’s what awaits you at SnT
• A stimulating learning environment. Here post-docs and professors outnumber PhD students. That translates into access and close collaborations with some of the brightest ICT researchers, giving you solid guidance
• Exciting infrastructures and unique labs. At SnT’s two campuses, our researchers can take a walk on the moon at the LunaLab, build a nanosatellite, or help make autonomous vehicles even better
• The right place for IMPACT. SnT researchers engage in demand-driven projects. Through our Partnership Programme, we work on projects with more than 45 industry partners
• Multiple funding sources for your ideas. The University supports researchers to acquire funding from national, European and private sources
• Competitive salary package. The University offers a 12 month-salary package, over six weeks of paid time off, health insurance and subsidised living and eating
• Be part of a multicultural family. At SnT we have more than 60 nationalities. Throughout the year, we organise team-building events, networking activities and more

In Short
• Work Hours: Full Time 40.0 Hours per Week
• Location: Kirchberg
• Job Reference: UOL04027
• Start Date: as early as possible

How to Apply
Applications should be submitted online and include:
• Curriculum Vitae
• Cover letter
• Contact Information of 2 referees
All qualified individuals are encouraged to apply. Early application is highly encouraged, as the applications will be processed upon reception. Please apply ONLINE formally through the HR system. Applications by email will not be considered. For further information please contact: Djamila.aouada@uni.lu

The University of Luxembourg embraces inclusion and diversity as key values. We are fully committed to removing any discriminatory barrier related to gender, and not only, in recruitment and career progression of our staff.

About the University of Luxembourg
The University of Luxembourg aspires to be one of Europe’s most highly regarded universities with a distinctly international and interdisciplinary character. It fosters the cross-fertilisation of research and teaching, is relevant to its country, is known worldwide for its research and teaching in targeted areas, and is establishing itself as an innovative model for contemporary European Higher Education. It`s core asset is its well-connected world-class academic staff which will attract the most motivated, talented and creative students and young researchers who will learn to enjoy taking up challenges and develop into visionary thinkers able to shape society.

SnT is a leading international research and innovation centre in secure, reliable and trustworthy ICT systems and services. We play an instrumental role in Luxembourg by fueling innovation through research partnerships with industry, boosting R&D investments leading to economic growth, and attracting highly qualified talent. We’re looking for people driven by excellence, excited about innovation, and looking to make a difference. If this sounds like you, you’ve come to the right place!

Your Role
The successful candidates will join the Computer Vision, Machine Intelligence and Imaging (CVI2) headed by Prof. Djamila Aouada in order to carry out research in the general area of Computer Vision. Multiple positions are open. CVI2 offers the opportunity to work on multiple projects (projects with industrial partners such as Lift-Me Off, ARTEC 3D and DataThings and/or national and international academic projects). All projects require conducting full scale experiments, including real-time implementation, data acquisition, training and validation at the SnT Computer Vision Lab. CVI2 is a young group composed of highly motivated and active members. Their work focuses on innovative research topics such as 3D shape modelling, 6DOF object pose estimation, human behavior understating, and deep learning and is disseminated in top-tiers venues.

- Shaping research directions and producing results
- Attracting funding in cooperation with industrial partners
- Participating in proposal writing
- Coordinating research projects and delivering outputs
- Disseminating results through scientific publications
- Providing guidance to PhD and MSc students
- Participating to the teaching activities
- Providing support in setting up and running experiments in the SnT Computer Vision laboratory
- Proposing and implementing real-time solutions
- Participating in organizing relevant workshops and demonstrations

Your Profile
- A PhD degree in Electrical Engineering, Computer Science, Applied Mathematics or a related field
-Competitive research record in computer vision and/or image/signal processing focusing on one or more of the following topics (Computer vision, Pattern recognition, Deep learning/machine learning, Computer graphics, etc.)
- Experience with European projects (FP7/H2020), national/international projects and/or industrial project
- Strong mathematical background
- Experience with machine learning algorithms
- Commitment, team working and a critical mind
- Strong development skills in Python, Matlab or/and C++
- Familiarity with deep learning frameworks such as Pytorch and Tensorflow
- Fluent written and verbal communication skills in English are mandatory

Here’s what awaits you at SnT
- A stimulating learning environment. Here post-docs and professors outnumber PhD students. That translates into access and close collaborations with some of the brightest ICT researchers, giving you solid guidance
- Exciting infrastructures and unique labs. At SnT’s two campuses, our researchers can take a walk on the moon at the LunaLab, build a nanosatellite, or help make autonomous vehicles even better
- The right place for IMPACT. SnT researchers engage in demand-driven projects. Through our Partnership Programme, we work on projects with more than 45 industry partners
- Multiple funding sources for your ideas. The University supports researchers to acquire funding from national, European and private sources
- Competitive salary package. The University offers a 12 month-salary package, over six weeks of paid time off, health insurance and subsidised living and eating
- Be part of a multicultural family. At SnT we have more than 60 nationalities. Throughout the year, we organise team-building events, networking activities and more

In Short
Contract Type: Fixed Term Contract
Location: Kirchberg
Job Reference: UOL03715
Start Date: as early as possible

Further Information
Applications should be submitted online and include:
- Curriculum Vitae
- Cover letter
- Contact Information of 2 referees
- All qualified individuals are encouraged to apply.
Early application is highly encouraged, as the applications will be processed upon reception. Please apply ONLINE formally through the HR system. Applications by email will not be considered. For further information please contact: Djamila.aouada@uni.lu

The University of Luxembourg embraces inclusion and diversity as key values. We are fully committed to removing any discriminatory barrier related to gender, and not only, in recruitment and career progression of our staff.

About the University of Luxembourg
The University of Luxembourg aspires to be one of Europe’s most highly regarded universities with a distinctly international and interdisciplinary character. It fosters the cross-fertilisation of research and teaching, is relevant to its country, is known worldwide for its research and teaching in targeted areas, and is establishing itself as an innovative model for contemporary European Higher Education. It`s core asset is its well-connected world-class academic staff which will attract the most motivated, talented and creative students and young researchers who will learn to enjoy taking up challenges and develop into visionary thinkers able to shape society.

PhD positions in Digital Media Technology
Ireland

Scholarship: Full payment of university fees and a tax-free stipend of €18,500 per annum for four years. In addition, a generous budget for conference travel, equipment, training, placement maintenance and publication costs is provided.
Positions: These 28 positions are being advertised as part of the Science Foundation Ireland-funded Centre for Research Training in Digitally-Enhanced Reality (d-real). Successful applicants will form a cohort-based doctoral programme involving five leading universities in Ireland –Dublin City University, NUI Galway, Trinity College Dublin, Technological University Dublin and University College Dublin
About the programme: Multimodal digital media, across video, text, image, speech and Virtual/Augmented Reality (VR/AR) content, are rapidly reshaping our working and living environments. Seamlessly blending digital media and interaction within the physical world offers disruptive potential to enhance our effectiveness, efficiency and quality of engagement in everyday life. The d-real programme is an innovative, industry partnered, research training programme that equips PhD students with deep ICT knowledge and skills across Digital Platform Technology, Content and Media Technology and their application in Industry sectors. d-real postgraduate students will make research breakthroughs in areas such as multimodal interaction, multimodal digital assistants, multilingual speech processing, real-time multilingual translation and interaction, machine intelligence for video analytics and multimodal personalisation and agency.
Topics: The d-real website lists the 28 available projects, giving details on the supervision team and a brief descriptor of the scope of the PhD position.
Application procedure: Applications are to be made using the form provided on our ‘Apply to d-real’ webpage. You will be asked for personal details, academic track record, a personal statement and to list your top three topic preferences.
Deadline: Rolling deadline, second call closing at 17.00 (Irish time) on Wednesday 22nd April 2021.
Queries: For queries about the programme please contact the programme manager, Stephen.Carroll@d-real.ie. For queries about the projects themselves please contact the primary supervisor of the particular project.

Closing date: 30th of April 2021

Description:
Medical imaging modalities such as Magnetic Resonance Imaging (MRI) often produce complex image data in a higher-dimensional format, e.g. diffusion MRI or functional MRI. For the computationally demanding post-processing of such data, we use modern machine learning techniques like convolutional neural networks, graph convolutional networks, and reinforcement learning. This project will deal with developing, adapting, and applying such techniques to imaging data from patients with neurodegenerative diseases, available to us thanks to our close cooperation with Karolinska Institute.

Requirements
A doctoral degree or an equivalent foreign degree, obtained within the last three years prior to the application deadline (With some exceptions for special reasons such as periods of sick or parental leave, kindly indicate if such reason exists in your resume).
The candidate must have a strong background in at least one of the following areas: neuroimaging including connectomics, medical image processing, machine learning or a similar subject. Proficiency in English orally and in writing is required to present and publish research results.

We prefer a candidate with:
Strong research qualifications
Good programming skills, in particular with libraries used for deep learning
Collaborative abilities
Experience of working in a cross-disciplinary setting
Independence
Teaching abilities
Awareness of diversity and equal opportunity issues, with specific focus on gender equality
Great emphasis will be placed on personal competency.

Application
Log into KTH's recruitment system in order to apply to this position. More information can be obtained in the official ad:

https://www.kth.se/en/om/work-at-kth/lediga-jobb/what:job/jobID:389800/…

City: Shanghai
Organizational Unit: School of Data Science, Fudan University
Duration: More than 1 year
Language Requirements: English

This post-doctoral project is mainly aimed at the development and verification of deep learning models and image processing methods for liver cancer and other cancer histopathology image data. Machine learning and deep learning technologies are the core technologies of the project. After being selected as a postdoc, you need to participate in the implementation and evaluation of machine learning/deep learning models, and contribute to the development of new methods and strategies in this field. It is suitable for those who are interested in developing careers in the interdisciplinary field of machine learning and medical image analysis.
Researchers who have successfully received funding from this project will join an interdisciplinary research team and work closely with clinical departments and other national and international research groups.

Requirement:
• Have or expect to obtain a doctorate degree (or equivalent) in a related discipline, and have a strong interest in the quantitative aspects of medical research

• Have relevant knowledge and research experience in related fields (such as machine learning, artificial intelligence, computer vision, biostatistics, etc.)

• Experience in large-scale biomedical data analysis or application of machine learning/deep learning/AI

• Experience in cancer-related research or medical image research

• Able to work together as part of a team, complete tasks independently, and be able to organize and prioritize tasks with minimal supervision

• Requires excellent written and oral communication skills in English

• Should have knowledge and experience in Python programming, preferably with work experience in commonly used deep learning frameworks, such as Tensorflow/Keras or Pytorch,

Salary:
We will provide a competitive salary according to the applicant's background, and support the applicant to actively apply for special funding support for postdoctoral students from Shanghai and the nation, as the additional salary.

Application Material
Contains the following documents (English or Chinese are acceptable)

• A complete resume, including the thesis defense date, thesis title, previous academic positions, academic titles, current positions, academic honors and academic organization work
• Complete academic dissertation publication list
• Summary of current work (no more than one page)

Contact:
Xiaoyu Nie, xiaoyunie@fudan.edu.cn
Yanwei Fu, yanweifu@fudan.edu.cn

Company
Cloud to Street is the world’s leading remote flood mapping platform. We use global satellites and remote sensing AI to monitor flood risk and detect worldwide floods in real-time. Seeded by Google, we have been used by governments across almost 20 countries for disaster relief efforts. Partnering with top insurers, we are now launching the first commercial parametric flood insurance product to better protect climate-vulnerable communities.

Role
We are looking for an experienced Machine Learning Engineer to help us scale up our Deep Learning efforts to turn optical and radar satellite imagery into actionable insights. In this role, you will take ownership of large projects in Cloud to Street’s Deep Learning agenda - building the full pipeline from training data collection to model training and testing. You will work with a team of scientists and engineers with expertise in Machine Learning, remote sensing, radar and hydrology to turn petabytes of satellite data into meaningful information to empower the world’s most vulnerable communities.
‍
This role is based in Brooklyn, NY and is remote until further notice. Remote work is possible within UTC -5 to UTC +1 time zones (Eastern Standard Time to Central European Time).

Who You Are
2+ years of job experience training Deep Learning algorithms for Computer Vision (CNNs)
Strong track record (e.g. own projects, Kaggle, …) of distilling data into algorithms and results
Excellent in Python and Deep Learning Frameworks (PyTorch favored)
Experience in Data Engineering with open source geospatial Python packages prefered
Self-directed with a focus on getting things done without ego
Prioritize justice, diversity, science, and solidarity with vulnerable communities

Responsibilities
Build Deep Learning based solutions to problems including: flood detection, cloud detection, super-resolution and gap filling
Automate the selection of the right additional training data to be labeled and review the quality of annotations from our partners
Integrate successful experiments and algorithms into the C2S product
Present findings in an accessible way to science and product teams
Evaluate, implement and test new approaches emerging from competitions or recent papers

To Apply
Send your resume to hiring@cloudtostreet.info with Machine Learning Engineering in the subject line. Let us know why you would like to join Cloud to Street and how you can best contribute. Applications will be open until the position is filled, with the goal of hiring the right candidate as soon as possible.

Cloud to Street is devoted to building an inclusive and diverse company. Black, Indigenous, and people of color; women, queer people, and all gender identities, and individuals with disabilities are especially encouraged to apply.

The subject of ‘fairness’ in artificial intelligence (AI) is a relatively new but fast-growing research field. It refers to assessing AI algorithms for potential bias based on demographic characteristics such as race, and the development of algorithms to address this bias. With AI models starting to be deployed in the real world it is seen as essential that its benefits are shared equitably according to race, gender and other demographic characteristics, and so efforts to ensure fairness of deployed models have generated much interest and some controversy (e.g. https://www.bbc.co.uk/news/technology-55164324). Most applications to date have been in computer vision, although some work in healthcare has started to emerge.

AI-based quantification of cardiac structure and function is also an active research area, and the success of AI in this field has meant that it is currently moving towards wider clinical translation. At the same time, it has long been well understood that cardiac structure and function, as well as the mechanisms leading to cardiovascular disease, vary according to demographic characteristics such as gender and race. Therefore, it is surprising that no work to date has investigated potential bias in AI models for cardiac image analysis. The aim of this project is to investigate this possibility, with a focus on cardiac magnetic resonance imaging (MRI), as well as to develop novel tools for mitigating the bias, thus creating fairer tools for clinical use.

Candidates for this position are expected to have strong computational skills, experience in or a desire to learn about AI and machine learning as well as a commitment to advancing the fairness of AI algorithms in healthcare.

Eligibility criteria:

Candidates who meet the eligibility requirements for Home (UK) Fee status will be eligible to apply for this project. Home students will be eligible for a full UKRI award, including fees and stipend, if they satisfy the UKRI criteria below, including residency requirements. To be classed as a Home student, candidates must meet the following criteria:

be a UK National (meeting residency requirements), or
have settled status, or
have pre-settled status (meeting residency requirements), or
have indefinite leave to remain or enter.

More details: https://www.kcl.ac.uk/study/funding/fairness-in-ai-for-cardiac-imaging

Job Description
The Mask Metrology Team at Intel Mask Operations is looking for someone who is primarily a software engineer but also who preferably has some background in other relevant areas of science/engineering to work on nanometer-scale computer vision and metrology applications.
This position is not in a software group and requires someone willing to work relatively independently, help to define requirements, implement new features and help to ensure that the software is reliable by developing and implementing test plans. Because this is a manufacturing facility you should also be prepared to document any changes to software running in the production environment and review the changes during meetings with internal stakeholders. In this position you would be responsible for design/selection of algorithms and implementation in software of those algorithms for analysis of images from inspection, registration and critical dimension measurement tools.

Qualifications
Candidate must possess a Master’s degree in Mechanical Engineering, Chemical Engineering or Science discipline such as Physics, Material Science. A PhD degree is preferred but not necessarily required.
Minimum of 2 years of experience in C/C++, with both Linux and windows development environments.
Minimum of 1 year of experience working on large software projects as part of a team.
Experience with image processing or computer vision projects in both C++ and Python is preferred.
Previous experience in math/statistics, computational geometry, machine learning for image analysis, graphics, GUI design, scientific computing, and numerical optimization.

Application link: https://jobs.intel.com/ShowJob/Id/2812021/IMO-Metrology-Automation-Engi…

About the position:
The postdoctoral fellowship will be held at the Department of ECE (https://www.ece.queensu.ca/index.html) and Ingenuity Labs Research Institute (https://ingenuitylabs.queensu.ca). The project is focused on deep learning for human understanding, for instance, affective computing, identity recognition, activity analysis, and pose estimation. The research will be carried out in the Ambient Intelligence and Interactive Machines (Aiim) lab, directed by Dr. Etemad. To learn more about some of the ongoing projects or recent publications out of Aiim, please visit http://aiimlab.com and http://aiimlab.com/publications.html

About Queen’s University:
Queen’s University is one of Canada’s leading research-intensive universities with a global reputation and is a recognized leader in Canadian higher education. The Department of Electrical and Computer Engineering has 30 full-time and 8 cross-appointed faculty, 756 undergraduate students, and 180 graduate students. Queen’s historic campus is located in the heart of the vibrant Kingston community in the Thousand Islands region of South Eastern Ontario. Queen’s is positioned centrally with respect to three major metropolitan areas: Toronto, Montreal, and Ottawa.

Qualifications:
• PhD in CE, CS, EE, or a related field
• Experience in machine learning, deep learning, and computer vision
• Algorithm development using Python (TensorFlow, PyTorch, Keras)
• Strong written and oral communications skills
• Prior publications in top-tier venues such as CVPR, ICCV, ECCV, NeurIPS, AAAI, ICLR, ICML, IJCAI, FG, WACV, IEEE Transactions.

Responsibilities:
• Conducting research on deep learning and computer vision
• Authoring/co-authoring high-quality papers
• Liaising with industry partners and sponsors
• Leading/advising junior researchers in the lab

How to apply:
Please send your full CV to ali.etemad@queensu.ca with the email title: Postdoc Position Inquiry