Job Board

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

Salary package: $99,809 - $113,165 per annum plus an additional 17% Superannuation.
Term: Fixed Term, Full time (1 Years to 2 Years)

The Australian National University is seeking to recruit a full time Research Fellow in the areas of 3D Computer Vision and Deep Learning to join the ANU computer vision and machine learning research group.

You will be responsible for developing new approaches for 3D computer vision algorithms and implementing and evaluating practical systems targeting at augmented reality and/or autonomous driving applications.

You will have an outstanding opportunity to work in one of the world's top computer vision groups on the exciting new topics of 3D reconstruction and deep learning. You will be working with a collaborative team of world leading academics, early career researchers and outstanding PhD students.

You should possess a recent PhD degree, or be near completion, in 3D computer vision, machine learning, or a relevant subject, together with a strong publication record, relative to opportunity, at primer computer vision, machine learning, or robotics conferences (CVPR, ICCV, ECCV, NeurlPS, ICLR, ICRA, RSS).

More details about the position and application process can be found on the "More Information" link below.

A four-year PhD position is available at the Department of Computer Science in Gjøvik. The PhD position is focused on research areas of mixed realty, edge computing, and artificial intelligence.
The focus of research will be to investigate: 1) a novel mixed reality pipeline leveraging edge architectures to handle vast amounts of data and provide high quality of experience to users; and 2) applying AI methods and leverage context-awareness for mixed reality applications.

The position reports to the Head of the Department.

Full-time CV Research position available at Qualcomm based in San Diego. A PhD degree is required upon start.
Contact Dr. Dashan Gao at dgao@qti.qualcomm.com, if interested.
Apply online at https://qualcomm.wd5.myworkdayjobs.com/en-US/External/job/San-Diego/Res…

Full-time CV Research position available at Qualcomm based in San Diego. A PhD degree is required upon start.
Contact Dr. Dashan Gao at dgao@qti.qualcomm.com, if interested.
Apply online at https://qualcomm.wd5.myworkdayjobs.com/en-US/External/job/San-Diego/Res…

We are looking for good candidates for the position as Assistant Professor (tenure track) in Computer Vision with focus on Machine Learning.
Application deadline May 11.
Note that Swedish universities leave all IPR with the employee, which gives unique opportunities for entrepreneurship!

Job Overview:

Qualcomm's Multimedia R&D and Standards Group is seeking candidates for its Computer Vision team in Shanghai, China. The team develops new algorithms, architectures and systems for computer vision application running in an embedded systems environment targeted primarily to devices operating in mobile, XR, automotive and IOT environments.

The candidates are expected to work on the following aspects:
1) Utilizing modern machine learning techniques for computer vision tasks
2) Development of concept proving demo on Qualcomm platform
3) Tackling practical issues in terms of accuracy and efficiency for specific application scenarios to make the computer vision technology ready for commercialization
4) Tracking cutting-edge computer vision and machine learning techniques and new emerging application fields
5) Proposing new ideas in algorithm /application for technology commercialization and/or patent application

Qualification:
1) Strong background and hands-on R&D experience in one or more of the following Computer Vision related areas：
1.1) Biometrics: Face/ Fingerprint recognition and anti-spoofing
1.2) Hand / body detection and 2D/3D pose estimation
1.3) Object detection/ tracking
1.4) Segmentation
2) Knowledge or experience in ultrasonic signal processing, transmission and acoustic imaging theory is a plus
3) PhD degree is preferred but Master with top-level conference / journal publication in CV/ ML area can be considered.
4) Proficiency in Python and C++ is a must. Java/ Script languages are plus.
5) Proficiency in Pytorch or Tensorflow is a must.
6) Experience with On-device deep learning model deployment is a plus
7) Experience with Android / Linux / QNX development is a plus
8) Experience with performance optimization with ARM/ DSP/GPU/NPU is a plus

https://qualcomm.wd5.myworkdayjobs.com/External/job/Shanghai/Machine-Le…

Categories: Academic
Classification: Academic Level B
Salary package: $99,809 - $113,165 AUD per annum plus additional 17% Superannuation
Term: Fixed Term, Full time (1 years ~ 2 years)

The Australian National University is seeking to recruit a full time Research Fellow in the areas of 3D Computer Vision and Deep Learning to join the ANU computer vision and machine learning research group. You will be responsible for developing new approaches for camera localisation and 3D computer vision algorithms and implementing and evaluating practical systems targeting at augmented reality and/or autonomous driving applications.

You will have an outstanding opportunity to work in one of the world's top computer vision and machine learning groups on the exciting new topics of 3D reconstruction and deep learning. You will be working with a collaborative team of world leading academics, early career researchers and outstanding PhD students. You should possess a recent PhD degree, or be near completion, in 3D computer vision, machine learning, or a relevant subject, together with a strong publication record, relative to opportunity, at primer computer vision, machine learning, or robotics conferences (CVPR, ICCV, ECCV, NeurlPS, ICLR, ICRA, RSS).

Advertised: 05 Mar 2021 09:00:00 AM AUS Eastern Daylight Time
Applications close: 12 Apr 2021 11:55:00 PM AUS Eastern Standard Time

Intelligent Automation, Inc. (IAI) has an open full-time position for a Research Scientist and Senior Research Scientist in computer vision and machine learning. We are looking for an outstanding self-motivated researcher with a Masters or Doctorate degree in Electrical Engineering or Computer Science with a background in computer vision and machine learning.

You will be working with the multi-disciplinary team of scientists and engineers to conduct R&D in the fields of video analytics, machine learning, robotics perception and AI. We have active research and development projects where we design, integrate, test, and deploy state-of-the-art systems for a range of applications, including image and video analytics, artificial intelligence, scene understanding, perception for autonomous systems, healthcare, training, and simulation.

The desired candidate should have a strong publication record in computer vision particularly in the areas of deep learning, object detection, tracking and classification, segmentation, cross-modality inference, self-supervised learning, activity recognition, facial analysis, biomedical image analysis, and robotic vision. A solid background in programming is important.

CITIZENSHIP / VISA STATUS: Applicant must be a US Citizen or US Permanent Resident

JOB DUTIES
• Conduct research and development in the area of computer vision and image processing
• Design, implement, and integrate computer vision and machine learning algorithms and prototypes
• Interact with and support multiple research teams
• Support program management and business development efforts by writing reports and presenting to customers
REQUIRED EXPERIENCE & EDUCATION
• Masters or Doctorate degree in computer science, electrical engineering, computer engineering, mathematics or other related field
• Minimum 3 years of hands-on experience in research, engineering, or research & development
DESIRED SKILLS
• Proficiency in Python, C++, and MATLAB
• Minimum 3 years of experience with computer vision techniques such as object recognition, segmentation, classification, and tracking.
• Experience with machine learning or deep learning models, such as CNNs, RNNs and GANs.
• Proficient technical writing and strong communication skills
• Familiarity with computer vision libraries and machine learning framework, such as OpenCV, PyTorch, and TensorFlow.
• Experience with geospatial image analysis, biomedical and healthcare image analysis, and embedded vision development.
ABOUT IAI: Intelligent Automation, Inc. (IAI) is a technology innovation company headquartered in Rockville, MD, conducts state of the art research and product development in the areas of Robotics, Signal Processing and Control, Sensor Technology, Distributed Intelligent Systems and other areas (visit www.i-a-i.com). We specialize in providing advanced technology solutions and R&D services to federal agencies, and corporations throughout the United States and internationally. IAI's core R&D areas include: Air Traffic Management, Big Data and Social Media Analytics, Control and Signal Processing, Cyber Security, Education and Training Technologies, Health Technologies, Modeling and Simulation, Networks and Communications, Robotics and Sensor Systems. For more information on IAI, please visit www.i-a-i.com.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status. IAI is an EEO/AA employer.

Apply at: https://www.linkedin.com/jobs/view/research-scientist-computer-vision-m…

The Technology department of NORCE Norwegian Research Centre AS is looking for a PhD candidate for a 3-year period in connection with the project ULEARN “Unsupervised Lifelong Learning”. The candidate is expected to start on 1 July 2021.

Previous research in both supervised and unsupervised learning assumes that training data have already been collected, and uses such training data to make predictions. The learning algorithm makes predictions, however typically without taking into account that the circumstances under which the data are acquired may have changed.

Furthermore, existing evolutionary algorithms manipulate a population of relatively simple structured candidate solutions, representing e.g. numerical parameter vectors or, in case of genetic programming, simple computer programs. Such representations are not sufficient for representing and evolving learning architectures and hence do not account for the needs of dynamic lifelong learning in software systems.

The PhD research should tackle on optimizing learning processes and handle changing conditions throughout lifetime. Moreover, the research should elaborate on evolutionary learning to go beyond this limitation by combining evolution and computational self-awareness. It aims to provide systems that learn and adapt their architecture during their lifetime on an ongoing basis, based on their sensed experiences and the internal models that they build. A self-aware system architecture addresses the question of how numerous interacting learning processes are structured, w.r.t. each other and the system's machinery for interaction with the world i.e. sensors/actuators and for a given task. The evolutionary algorithm will be combined with the self-aware system to allow for it to “try” parametric and structural variations (“mutations”) of itself and “select” such a variation once it demonstrates beneficial in terms of one or more continuously updated “fitness” measures of the evolving learning software system. Computer vision applications are targeted for validating the feasibility of the approach.

We offer an attractive Research Associate (Postdoc) position in close cooperation with our industrial partner POST Group. POST Group is one of the largest employers in Luxembourg. It has a well-established reputation and is firmly rooted in Luxembourg. It is also an innovative company that adopts an open-minded approach to the world thanks to its constantly evolving activities (www.postgroup.lu/home). The successful candidate will join the Computer Vision, Machine Intelligence and Imaging (CVI²) research group headed by Prof. Djamila Aouada to conduct exciting research in the field of Computer Vision.
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! The selected candidate will help out in shaping research directions and carry out high-impact research within the SnT and Post R&D activities. The successful candidate will perform the following tasks:
• Shaping research directions and producing results
• Disseminating results through scientific publications
• Attracting funding in cooperation with industrial partners
• Participating in proposal writing
• Coordinating research projects and delivering outputs
• Providing support in setting up and running experiments
• Implementing real-time solutions
• Providing guidance to PhD and MSc students
• Organizing relevant workshops and demonstrations
• Participating to the teaching activities

Your Profile
• A PhD degree in Electrical Engineering, Computer Science, Applied Mathematics or a related field
• Competitive research record in Computer Vision, preferably with publications at top-tier CV/ML conferences/journals
• Strong development skills in Python/C++
• Strong mathematical background
• Broad experience with machine learning algorithms and deep learning concepts
• Previous experience with Generative Adversarial Networks (GANs)
• A particular interest in DeepFake and DeepFake detection approaches
• Commitment, team working and a critical mind
• Fluent written and verbal communication skills in English are mandatory

In Short
• Contract Type: Fixed Term Contract 24 Month
• Work Hours: Full Time 40.0 Hours per Week
• Location: Kirchberg
• Job Reference: UOL04040

Applications, written in English should be submitted online following this link
and should include:
• Curriculum Vitae (including your contact address, work experience, publications, etc.)
• Cover letter indicating the research area of interest and your motivation
• A research statement (max 1 page)
• Contact information for 3 referees, including details (name, email address, etc.)
• Github/Gitlab webpage listing completed projects on Computer Vision

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.
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.

For further information you may check: www.securityandtrust.lu or contact Djamila.Aouada@uni.lu

We offer an attractive Research Associate (Postdoctoral) position in close cooperation with our industrial partner Artec3D. Artec3D is a global leader in handheld and portable 3D scanners and has been at the forefront of developing innovative 3D technology since 2007 (www.artec3d.com). The successful candidate will join the Computer Vision, Imaging and machine Intelligence (CVI²) research group (http://cvi2.uni.lu) headed by Prof. Djamila Aouada to conduct exciting research in the field of 3D Computer Vision. He/she will help out in shaping research directions and carry out high-impact research within the SnT and Artec3D R&D activities. The CVI² research group is very active in 3D Computer Vision research community, by conducting high-impact research and organising relevant workshops and challenges such as SHARP2020 in conjunction with ECCV2020 (https://cvi2.uni.lu/sharp2020/) and SHARP2021 in conjunction with CVPR2021 (https://cvi2.uni.lu/sharp2021/). The successful candidate will perform the following tasks:

· Shaping research directions and producing results in the field of 3D Computer Vision. Topics include but are not limited to: 3D shape modelling, 3D mesh analysis, 3D CAD modelling, 3D reverse engineering, Geometric deep learning
· Disseminating results through scientific publications
· Coordinating research projects and delivering outputs
· Participating in writing proposals
· Participating to the teaching activities
· Providing support in setting up and running experiments
· Implementing real-time solutions
· Providing guidance to PhD and MSc students
· 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, preferably with publications at top-tier CV/ML conferences/journals (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, TPAMI, TNNLS, etc.)
· Strong development skills in Python/C/C++
· Strong mathematical background
· Broad experience with machine learning algorithms and deep learning concepts
· Experience with at least one of the following deep learning frameworks: TensorFlow, PyTorch, Keras
· Experience with relevant libraries for 3D mesh and point cloud analysis
· Previous experience in 3D Computer Vision
· A particular interest for 3D CAD modelling
· Commitment, team working and a critical mind
· Fluent written and verbal communication skills in English are mandatory

In Short

· Contract Type: 2 years contract
· Work Hours: 40 hours/week
· Very competitive salary package
· Location: Kirchberg, Luxembourg
· Apply following this link

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.

Hello,

We are seeking candidates who are interested in
developing deep learning algorithms for improving the
registration/alignment of our
2D/3D MRI and microscopy images.

More information: on our lab web-page
http://bia.riken.jp or institute web-page
Riken Careers

Best wishes,

Henrik

We are currently looking for Computer Vision and Machine Learning researchers to join our team in Staines-upon-Thames. This is a good opportunity to work on next-generation mobile devices from Samsung.

The prospective engineer will investigate vision techniques for content creation and image manipulation, e.g. style transfer, and processing of live camera frames and images on PC and mobile environment. The prospective engineer will have an opportunity to work in production environments and solve industry-relevant problems.

As a Computer Vision and Machine Learning Intern you will:

Review the state of the art computer vision research papers and develop prototype solutions.
Development of software and algorithms for computer vision, image processing and deep learning models
Have technical responsibility for one or more significant sections of the assigned project
Translate complex functional and technical requirements into detailed design

Skills and Qualifications

Skills and attributes:

Required Skills

Masters, Ph.D., or equivalent experience in Computer Vision or Machine Learning (Computer Science, Mathematics, Engineering, etc.)
Programming proficiency one or more of programming language and APIs like C++/Java/Python
Computer vision, machine/deep learning or related fields
Excellent communication, teamwork and a results-oriented attitude
Proficiency in problem-solving and debugging
Desirable Skills

Content creation and image manipulation, e.g. style transfer
Computational photography, image segmentation and 3-D vision
Experience in using Deep Learning libraries like Pytorch and/or TensorFlow
Experience in Android application development

Job description
Magnetic resonance elastography (MRE) in the brain is a technique of magnetic resonance imaging (MRI) in which mechanical properties of the brain tissue are estimated non-invasively. Currently, MRE reconstruction is challenging, especially for young people. Preliminary studies have shown that artificial intelligence (AI) is promising for improving MRE reconstruction. In this project, we aim at characterizing the mechanical properties of the brain through MRE in people between 9-15 years old and at correlating them with risk factors for developing anxiety disorders. Thus, the main tasks of the candidate will be:
- Participate in the optimization, acquisition, and processing of images of the subjects in the study.
- Develop novel AI-based MRE reconstruction methods for increasing both accuracy and computational efficiency aiming at our target population.
- Perform correlation analyses between mechanics, predictors of anxiety, and brain connectivity measurements estimated from diffusion MRI and resting-state functional MRI.
- Report the results in the form of scientific manuscripts.

This project is a collaboration between Associate Professors Rodrigo Moreno (rodmore@kth.se) from the Division of Biomedical Imaging at KTH and Armita Golkar (armita.golkar@psychology.su.se) from the Department of Psychology at Stockholm University and 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: magnetic resonance elastography, neuroimaging, group-level statistical analysis of medical images, artificial intelligence/machine learning methods applied to medical images, or brain connectivity analysis. Proficiency in English orally and in writing is required to present and publish research results.

We prefer a candidate that

- Has good research qualifications
- Is familiar with image processing tools for neuroimaging
- Has good programming skills with libraries used for deep learning
- Can collaborate with professionals from diverse backgrounds
- Can work independently
- Can methodically organize and structure research data
- Is aware of diversity and equal opportunity issues, with specific focus on gender equality.

Great emphasis will be placed on personal competences.

Application
Log into KTH's recruitment system in order to apply to this position: https://www.kth.se/en/om/work-at-kth/lediga-jobb/what:job/jobID:387185/…

The application must include:

- CV including relevant professional experience and knowledge. The most relevant papers for the position must be listed.
- Copy of diplomas and grades from your previous university studies. Translations into English or Swedish if the original documents have not been issued in any of these languages.
- Brief account of why you want to conduct research, your academic interests and how they relate to your previous studies and future goals. Max two pages long.
- Contact information of two reference persons. We reserve the right to contact references only for selected candidates

Your complete application must be received at KTH no later than the last day of application (14th of April 2021), midnight CET/CEST (Central European Time/Central European Summer Time).

Company Overview
KLA is a global leader in diversified electronics for the semiconductor manufacturing ecosystem. Virtually every electronic device in the world is produced using our technologies. No laptop, smartphone, wearable device, voice-controlled gadget, flexible screen, VR device or smart car would have made it into your hands without us. KLA invents systems and solutions for the manufacturing of wafers and reticles, integrated circuits, packaging, printed circuit boards and flat panel displays. The innovative ideas and devices that are advancing humanity all begin with inspiration, research and development. KLA focuses more than average on innovation and in 2019 we invested 15% of sales back into R&D. Our expert teams of physicists, engineers, data scientists and problem-solvers work together with the world’s leading technology providers to accelerate the delivery of tomorrow’s electronic devices. Life here is exciting and our teams thrive on tackling really hard problems.

Responsibilities
KLA is seeking a motivated individual for an engineer position in a world-class algorithm group within the reticle product division (RAPID). This individual will utilize his/her skills in Machine Learning and Artificial Intelligence as well as Image Processing to develop and integrate algorithms into KLA’s state of the art inspection platforms. Responsibilities of this position include:
• Utilize advanced techniques in image processing, mathematics, and software to develop novel modeling, defect detection and optimization algorithms balancing between rigor and computational complexity through comprehensive data analysis.
• Deploy machine learning techniques to complement and enhance the performance of existing algorithms in optical and/or electron beam modeling and defect detection space
• Collaborate with software and computer groups to design and implement data management, model training and inference flow
• Improve accuracy and computational efficiency through iterations of data analysis and algorithm customization
• Bring forward creative ideas, develop production code and provide support as needed
• This candidate shall work tightly with the Milpitas and Ann Arbor project teams.

Qualifications
• Ph.D. in Applied Math, EE, Computer Science or related field
• 4 years of experience required in any two of the following: Image Processing, Deep Learning, or Optical Modeling (experience in all three is a plus)
• Knowledge of Machine Learning techniques and can bridge with conventional computer vision and image processing techniques
• Significant experiences in C++ production software under Linux is highly desired
• Familiarity with Data analysis and visualization tools is a plus
• Experience with linear and non-linear optimizations, is a plus
• Algorithm prototyping using MATLAB or Python is preferred
• Familiarity with GPU programming, is a plus
• Strong oral and written communications skills to interact with other development and applications engineers daily

Minimum Qualifications
Doctorate level degree with 3 + years of work experience OR Master's level degree with 6+ years of work experience OR Bachelor's level degree with 8+ years of work experience.

Send your resumes to sivaram.bose@kla.com

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
We offer attractive PhD candidate positions including industrial PhD positions conducting research in close cooperation with an industrial partner.

The successful candidates will join the Computer Vision, Machine Intelligence and Imaging (CVI2) headed by Prof. Djamila Aouada in order to pursue a PhD in the general area of Computer Vision. Multiple positions are open. They will carry out research in predefined topics contributing to CVI2’s activities in computer vision and pattern recognition. CVI2 offers the opportunity to work on industrial projects (with industrial partners such as Lift-Me Off, ARTEC 3D and DataThings) or national and international academic projects. 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.

The position holder will be required to perform the following tasks:

-Carrying out research in a predefined topic and producing results
- Disseminating results through scientific publications
- 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 master’s degree in Electrical Engineering, Computer Science, - Applied Mathematics or a related field
- Strong background in image/signal processing or/and in computer vision
- Strong programming skills in Python/Matlab/C/C++
- Strong mathematical background
- Familiarity with deep learning frameworks such Pytorch, Tensorflow
- Commitment, team working and a critical mind
- 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
But wait, there’s more!

Complete picture of the perks we offer
Discover our Partnership Programme
Discover CVI2’s research activities
In Short
Contract Type: Fixed Term Contract 3 Year
Location: Kirchberg
Job Reference: UOL03720
Start Date: as early as possible
Further Information
Applications should be submitted online and include:

- Curriculum Vitae
- List of three referees, including details (name and email address, etc.)
- Publication list
- Transcript of all modules and results from university-level courses taken
- Research statement and topics of particular interest to the candidate (300 words)
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.

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.

Further information
For further information you may check: www.securityandtrust.lu or contact Djamila.Aouada@uni.lu

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
- 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.

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.

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.