Job Board

IBM Watson Health Imaging - Senior Data Scientist

As part of the Watson Health Imaging division the Medical Imaging Data Scientist will be joining a highly entrepreneurial "Rapid Development team" where we are shaping the future of healthcare for the industry and for IBM. We are seeking individuals who will join the Care Advisor for Prostate Algorithm Development team and work with algorithm developers in Watson Health Imaging and IBM Research teams in USA, Canada and Haifa, Israel, to accelerate the creation of Care Advisor offerings in Watson Health Imaging portfolio.

IBM Watson Health is looking for talented individuals destined to usher in the next era of healthcare. We live in a moment of remarkable change and opportunity. The convergence of data and technology is transforming healthcare and life sciences organizations today. New opportunities are being created that never existed before to meet the demands of this transformation.
The Rapid Development Team is a group of AI Scientists and Software Developers within IBM Watson Health Imaging. In collaboration with cross-functional Watson Health teams, IBM Research and external partners, the team develops AI solutions that combine imaging and clinical data to enhance clinical decision making. The team is responsible for developing and validating robust and scalable cognitive services (text analytics and image analytics) and applications, including validation and evaluation of technologies being transferred from Research and other collaborators. We are looking for self-motivated and driven candidates that are passionate about working on cutting edge technologies and that thrive in a highly collaborative environment.

Responsibilities:

- Design and development of robust algorithms and techniques using image analytics, computer vision and machine learning
- Rapid development and validation of cognitive solutions by using and/or enhancing existing methodologies, frameworks and architecture
- Development of criteria for testing algorithm and system’s cognitive performance objectively from end-user and market perspective.
- Conduct performance evaluation and testing of algorithms and systems on test and real clinical data
- Work with clinical collaboration and joint development partners in Europe to develop cognitive solutions
- Support collection and annotation of data for algorithm development and evaluation
- Integration of cognitive systems and components in Watson Health architecture, including Watson Health cloud
- Planning, processing and performing all jobs in an efficient manner with minimum supervision
- Conduct product development in compliance with Watson Health’s methodology, practices and Quality Management system.

Requirements :

- 4+ years experience (post doctorate) with solving real-world problems using Data Analytics,
Computer Vision and Machine Learning
- Strong experience in Machine Learning, including deep learning and statistical models
- Strong Programming skills (Java/J2EE, C++, Python) and experience with software systems architecture, web services, web applications, and current software development tools, technologies and frameworks
- Strong publication record in peer-reviewed conferences and journals
- Demonstrated communication and cross-functional collaboration skills - Fluency in French;

DESCRIPTION: We're looking for ML engineers with Healthcare experience. You will work with multi-modality data, possibly from: EHR, Medical Imaging, or Genomics.

Ideal candidate would have:

1) Strong skills in model development and deployment, in addition to having experience in either of: (a) EHR, (b) 3D medical images (e.g. CT, MRI), or (c) Genomics. Candidates without healthcare experience who have excellent full stack ML experience will also be considered (please read on for more info).

2) MS or PhD in a related area, with relevant work experience after graduation. Work experience requirement is flexible for recent graduates with strong skills in ML and programming.

3) A key quality we're looking for is willingness to learn new things. The role might entail familiarizing yourself with a new data modality (e.g. you have previous experience with medical imaging and your new project requires you to learn genomics data science).

4) Model deployment skills: for some perspective on what the ideal applicant should know, please see: https://fullstackdeeplearning.com. If you're not well-versed with deployment at the moment but are willing to learn quickly, that is fine too.

5) An open mind, good communication skills in English, and accepting of others' ideas.

6) Strong team player: We believe a team wins or fails together, there are no individual victories or failures. It is therefore essential that the candidates must be willing to learn from or teach their colleagues and be willing to work for the team's success.

INTERVIEW: Our interview process entails assessment of ML and programming skills, in addition to questions on your relevant experience.

THE TEAM: You will join an internationally-trained team of Healthcare AI researchers, product managers, data scientists, and software engineers, in addition to medical doctors with management experience on full time staff. With confirmed world's most comprehensive population genome program (web: pgp.ae) with the Department of Health of UAE, and other Medical Imaging projects in the beginning stages, right now is an excellent time to join the team. This is a high growth role. We believe in merit of reason over rank – you will work collaboratively with your colleagues and team lead to collectively make useful decisions for the projects.

APPLICATION: Please send your resume or CV, and a few lines of text highlighting the relevance of your experience to the advertised role in an email.

BENEFITS: US $-standard competitive tax-free salary with additional perks e.g. excellent family health insurance, annual flight allowance etc.

ABU DHABI: Capital of UAE and located close to Dubai, Abu Dhabi is a family-friendly city that offers the right balance between megacity-convenience in a small-town liberal setting with access to two major international airports (Abu Dhabi and Dubai) offering non-stop flights to all parts of the world. Abu Dhabi is home to several world-class universities, schools, hospitals and recreation centers including New York University (NYU), Cleveland Clinic, The Louvre Museum, Ferrari World, Warner Brothers Theme Park, Yas Waterworld, and many others. With several pristine fine-sand beaches, multi-ethnic restaurants, a mangrove national park within the city, and mountains a short distance away, Abu Dhabi offers superb opportunities for work and play.

We are accepting applications for a 4-year Level A post-doctoral position, with a salary range from $86,587 to $94,588 per annum plus an employer contribution of up to 17% superannuation.

Build your research career within the Australian Institute for Machine Learning, School of Computer Science and contribute to an innovative project with important applications in medical image analysis

Be part of a research team investigating new deep learning modelling approaches to leverage real-world large-scale image data sets containing noisy and incomplete labels and imbalanced class prevalence – to enable the use of these data sets for modelling deep learning classifiers.

This project involves collaborating with international machine learning partners in Germany and Portugal, and an inter-disciplinary collaboration with the South Australian Health and Medical Research Institute (SAHMRI). This position is within the Australian Institute for Machine Learning, which is an institute that conducts state-of-the-art research in machine learning, computer vision, and medical image analysis, hosting the largest computer vision and image analysis research group in Australia.

The discoveries to be made in the project will significantly increase our understanding of deep learning theory regarding optimisation and noise models enabling the development of new applications that can use previously unexplored data sets. This project represents a unique opportunity to produce future expertise for the Australian workforce, not only in university research, but in industry.

As the successful applicant, you will develop innovative machine learning methods that can use real-world large-scale image data sets containing noisy and incomplete labels and imbalanced class prevalence. The majority of your work regards the development of novel machine learning methods, but you will also actively participate at the School of Computer Science by teaching courses, performing administrative activities and have co-supervision development opportunities.

To be successful you will need:

A PhD (or near completion) in Medical Image Analysis, Computer Vision, Machine Learning, Artificial Intelligence or other closely related areas with a first degree in Engineering, Computer Science or a related discipline
Expertise in programming machine learning methods, especially in Python (tensorflow and pytorch), C++ and Matlab
A record of quality research as evidenced by publications in leading journals and at conferences
Good interpersonal and communication skills with the ability to tailor communication skills when interacting with students, researchers, professional staff and external stakeholders
A strong work ethic, and the ability to work well independently, and as a member of a broader team, including with industrial partners
Enjoy an outstanding career environment

The University of Adelaide is a uniquely rewarding workplace. The size, breadth and quality of our education and research programs - including significant industry, government and community collaborations - offers you vast scope and opportunity for a long, fulfilling career.

It also enables us to attract high-calibre people in all facets of our operations, ensuring you will be surrounded by talented colleagues, many world-leading. Our work's cutting-edge nature - not just in your own area, but across virtually the full spectrum of human endeavour - provides a constant source of inspiration.

Our core values are honesty, respect, fairness, discovery and excellence. Our culture is one that welcomes all and embraces diversity, We are firm believers that our people are our most valuable asset, so we work to grow and diversify the skills of our staff.

In addition, we offer salary packaging; high-quality professional development programs and activities; and an on-campus health clinic, gym and other fitness facilities.

Learn more at: adelaide.edu.au/jobs

Your faculty's broader role

The Faculty of Engineering, Computer and Mathematical Sciences is a thriving centre of learning, teaching and research in a vast range of engineering disciplines, computer science - including machine learning - and high-level mathematics. Many of its academic staff are work leaders in their fields and graduates are highly regarded by employers.

Learn more at: ecms.adelaide.edu.au

If you want to change tomorrow, act today

Click the link to the online application form below (https://careers.adelaide.edu.au/cw/en/job/503710/internal-grantfunded-r…) and upload your responses to all selection criteria. Application close 11:55pm, 16 February 2020.

For further information

For a confidential discussion regarding this position, contact:

Gustavo Carneiro
Professor, School of Computer Science
P: +61 (8) 83136164
E: gustavo.carneiro@adelaide.edu.au

Scholarship: Full payment of university fees and a tax-free stipend of €18,500 per annum for four years. In addition, a budget for equipment, travel and training is provided.

Role: This position is being advertised as part of the Science Foundation Ireland-funded Centre for Research Training in Digitally-Enhanced Reality (D-REAL). The selected applicant will become part of a cohort-based doctoral programme involving five leading universities in Ireland – Trinity College Dublin, Dublin City University, NUI Galway, TU Dublin and University College Dublin. Further details on the programme here: d-real.ie.

Title of project: VRFaces: Next-generation performance capture for digital humans in immersive VR

Supervision Team: Dr Rachel McDonnell, Trinity College Dublin / Professor Noel O’Connor, Dublin City University

Description of topic: It is expected that immersive conferencing in virtual reality will replace audio and video in the future. By using embodied avatars in VR to act as digital representations of meeting participants, this could revolutionize the way business is conducted in the future, allowing for much richer experiences incorporating the interpersonal communication that occurs through body language and social cues. However, creating virtual replicas of human beings is still one of the greatest challenges in the field of Computer Graphics. The aim of this project is to advance the animation technology considerably to allow a user to truly “become” their virtual character, feeling ownership of their virtual face, with near cinema quality facial animation.

Skills requirements: Applicants will be expected to have skills in the following areas: computer graphics/vision, OpenGL, Unity or Unreal Engine 4, virtual reality, motion capture, machine learning, geometry processing, face recognition/tracking.

POSITION PURPOSE
• Dedicated to delivering Machine Learning projects within the CHEP Supply Chain.
• Dedicated to driving industry and market exploration into Machine Learning capabilities, assessing, leading feasibility study and applications of how it can be used in CHEP to further enhance our platform inspection capability across all CHEP platforms.

MAJOR / KEY ACCOUNTABILITIES
• Delivery of at least 2 Machine Learning projects per year for CHEP business across all platforms
• Demonstrate an ongoing understanding of Machine Learning technologies in current marketplace and how they can be applied to the CHEP business
• Research and on-board of technology suppliers for machine learning development and those that work in Machine Learning applications.
• Manage and lead Machine Learning development capital initiatives to support the technology development
• Facilitate and lead data gathering efforts and support testing during validation process

MEASURES
• Delivery of Machine Learning projects based on strategy and business need.

SCOPE
• Countries: Global to all CHEP Pallet business units
• Suppliers: Minimum of 2

AUTHORITY / DECISION MAKING
• Deliver value added machine vision projects corporately.
• Plan and deliver capital projects in excess of $100K in company assets.

CHALLENGES
• Utilizing existing hardware and images in addition to new image data gathering techniques to produce innovative image analysis models and algorithms.
• Development of ML approaches that improve the speed and accuracy of image algorithm development for inspection and quality control methods.

KEY CONTACTS
Process Engineering, including existing machine vision development team, Operations and Quality team

External:
External Technology Development and Data Annotation Suppliers

QUALIFICATIONS
• MS or PhD in Computer Science, Engineering, Mathematics or Statistics, with specialization in machine learning
• Proficient in Python or C/C++
• Proficiency in CV/ML libraries (OpenCV, Scikit-learn, Numpy, Pandas)
• Proficiency in Deep Learning frameworks (Tensorflow and Keras)
• Proficiency in implementing deep learning architectures for Image classification, Object detection and Object segmentation
• Demonstrated experience in scientific research related to Computer vision and Deep learning
• Scientific thinking and the ability to invent, implement, and lead technology developments in the field of computer vision and machine learning.
• Solid software development experience.
• Excellent written and spoken communication skills.

EXPERIENCE
• Minimum of 3 years of industrial experience in developing Computer Vision and Deep Learning applications in Python
• Experience in multi-facility, international organizations desired
• Experience in a diverse multi-cultural corporate environment desired
• Successful delivery of machine learning applications to internal or external customers

SKILLS AND KNOWLEDGES
• Strong Python/C++ programming capabilities
• Scientific understanding of Computer Vision algorithms and Deep learning architectures
• Ability to read scientific publications, understand and implement proposed solution
• Project Management
• Leadership: Ability to operate with little supervision and can make presentations at leadership level.
• Self-driven and strong problem-solving skills
• Team work
• Strong analytical skills and process focus

Desirable:
• Publications in top CV conferences and Journals (CVPR, ICCV, ECCV, NIPS, ICML, PAMI, etc.)
• Proficiency in Activity recognition and Object tracking
• 3D image algorithms experience
• Ability to work in a Matrix Organization

LANGUAGES
English
Desirable: Spanish

Black Sesame Technologies Inc (www.bst.ai) is a well-funded high-tech enterprise focused on the development and application of digital imaging, computer vision, artificial intelligence and system-on-chip (SOC) design core technologies. BST was founded in 2016. Its US office is located in Santa Clara, CA. We have several offices in Shanghai, Wuhan, Shenzhen, Chengdu in China and an office in Singapore as well. BST is committed to providing customers with high quality, safe and reliable technologies and solutions. Our products are used in mobile devices, automobiles and a variety of consumer electronics products. If you are imaginative, collaborative, self-motivated and interested in working in a startup environment, please come and join our world class team of scientists and engineers to solve high impact problems. The company is growing very fast. We currently have a few job openings in the following categories. The relevant skills and experience requirements are listed as examples.

1. Computer Vision engineer/scientist: face detection, facial landmark detection, face recognition, human pose estimation, gaze estimation, facial expression recognition, 3D face reconstruction, anti-spoofing, human action/activity recognition, object detection and tracking, semantic segmentation, stereo vision; familiar with OpenCV, C/C++ and Python;

2. Deep Learning engineer/scientist: familiar with state-of-art deep learning techniques and development platforms, e.g., CNN, RNN, LSTM, Tensorflow, Pytorch, model design and training, data preprocessing and augmentation, model compression and quantization; high performance computing, embedded processing and optimization; C/C++, Python, GPU programming, CUDA/OpenCL .

Fresh PhD or MS with related industry experience are preferred. We support H1b, O1 and green card application if needed. The company offers competitive compensation package and equity (i.e., stock options), 401k plan, health insurance, vision and dental plans, PTOs. If you are interested in any position or have any question regarding the application process, please contact lei.zhang@bst.ai.

Contribute to exciting and high visibility projects that will push the state-of-the-art in image and video understanding, computer vision, machine learning, deep learning, and data mining and reasoning. This will involve generation and evaluation of novel ideas, presentation of these ideas to peers and customers and participation in engineering these ideas for real-world systems. Our research group offers a dynamic, fun, and intellectually stimulating environment for cutting-edge research.

The main job responsibility of the candidate will be working with computer vision scientists and engineers to develop, evaluate, and optimize machine learning and deep learning methods for a wide range of computer vision tasks, including face detection/verification/recognition; face-based liveness detection and anti-spoofing; moving object detection and tracking; object classification/recognition/identification; 3D reconstruction; activity detection and classification; and scene classification and segmentation. Candidate should be conversant with the latest development in deep learning for visual recognition and video analytics, including the latest deep model compression and optimization techniques for edge inference and training. The ideal candidate possesses an impressive educational background and work experience in using machine learning and deep learning to solve computer vision problems, and can demonstrate both the breadth and the depth of knowledge that is required to solve challenging problems in real-world scenarios.

Candidate Profile
BS in Computer Science or Electrical Engineering, related field or equivalent experience, MS preferred

Past successful experience in applying machine learning and deep learning to solve computer vision problems

Ability to work with complex multi-faceted problems

Strong coding skills, including experience with Python, C/C++

Strong statistical background, a minor in math or statistics is a plus

Computer Vision, Machine learning, or Data Science coursework or experience required

Good data management skills and the ability to work with large disparate datasets

Must be a self-motivated worker and team player with good communication skills

ObjectVideo Labs offers competitive pay and a generous benefits package including health and welfare benefits, 401(k) with employer match, paid holidays, paid time off, and paid maternity/paternity leave. We offer a casual work environment, gym subsidy, education assistance program, and in-suite bike racks and showers.

ObjectVideo Labs is an equal employment opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other status protected by law.

Contribute to exciting and high visibility projects that will push the state-of-the-art in image and video understanding, computer vision, machine learning, deep learning, and data mining and reasoning. This will involve generation and evaluation of novel ideas, presentation of these ideas to peers and customers and participation in engineering these ideas for real-world systems. The successful candidate will also have ample opportunities to lead projects based on their generated ideas. Our research group offers a dynamic, fun, and intellectually stimulating environment for cutting-edge research.

Areas of interest include but are not limited to: face detection/verification/recognition; face-based liveness detection and anti-spoofing; moving object detection and tracking; object classification/recognition/identification; 3D reconstruction; activity detection and classification; and scene classification and segmentation. Candidate should be conversant with the latest development in deep learning for visual recognition and video analytics, including the latest deep model compression and optimization techniques for edge inference and training. The ideal candidate possesses an impressive educational background in related fields with a strong publication record, and can demonstrate both the breadth and the depth of knowledge that is required to solve challenging problems in real-world scenarios.

Candidate Profile
MS in Computer Engineering, Computer Science, Computer Vision, Robotics, related field or equivalent experience; PhD preferred.

Solid research background and experience in computer vision, machine learning, and image/video analysis algorithms.

Current knowledge of research literature in Computer Vision with a history of publication in the field.

Excellent written and oral communication skills also required.

ObjectVideo Labs offers competitive pay and a generous benefits package including health and welfare benefits, 401(k) with employer match, paid holidays, paid time off, and paid maternity/paternity leave. We offer a casual work environment, gym subsidy, education assistance program, and in-suite bike racks and showers.

ObjectVideo Labs is an equal employment opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other status protected by law.

Par­ti­cip­a­tion in the research activ­it­ies of the Remote Sens­ing Image Ana­lysis (RSiM) group in the field of machine learn­ing and big data man­age­ment for earth obser­va­tion. Devel­op­ment of image search and retrieval meth­ods and sys­tems for query­ing large-scale satelilite image archives in the com­pressed domain. Developed meth­ods will aim at enabling accur­ate and scal­able image index­ing and retrieval by effi­ciently char­ac­ter­iz­ing the high-spec­tral and spa­tial inform­a­tion. PhD thesis pre­par­a­tion is pos­sible.
Require­ments:
- suc­cess­fully com­ple­ted uni­ver­sity degree (Mas­ter, Diplom or equi­va­lent) in com­pu­ter sci­ence, com­pu­ter engi­nee­ring or a rela­ted field
- expe­ri­ence in machine lear­ning, dis­tri­bu­ted sys­tems and data­base tech­no­lo­gies
- solid pro­gramming skills
- fami­liar with at least one deep lear­ning frame­work (ten­sor­flow, caffe, pytorch)
- excel­lent com­mand of Ger­man and Eng­lish

Main Responsibilities:

- Work with senior experts in the area of Computer Vision and conduct state-of-the-art research in the field. Expect to learn and experience conducting top-tier research in a collaborative team-working environment;
- Contribute to patents, strong publications and transferring technologies into practical product solutions;
- Be ambitious to lead changes in future Healthcare with innovations.

Qualification Requirements:

- Currently pursuing an MS or PhD Degree in Computer Science, Computer Engineering, Biomedical Engineering, Statistics, Applied Mathematics, or other related fields;
- Self-motivated and demonstrated problem solving and critical thinking skills;
Familiarity with at least one mainstream deep learning toolkit, e.g., Pytorch, Tensorflow;
- Experience using Python and OpenCV;
- Proven track record of publications in the top computer vision venues is a plus;
- Experience with 6D pose estimation or 3D visual data processing is a plus;
- Good communication skills and team-work spirit.

At TU Dresden, the Chair of Machine Learning for Computer Vision offers a position for a

PhD Student Computer Vision

Tasks:
- Curiosity-driven basic research of fundamental problems in the fields of computer vision and image analysis
- Design and analysis of algorithms for solving these problems, exactly or approximatively
- Implementation, empirical analysis and comparison of these algorithms with respect to real data
- Publication of findings and insights in internationally leading conferences and journals
- Teaching assistance, esp. co-supervision of student research projects, and tutoring, in English.

Requirements:
- A very good university degree in mathematics or computer science or a related discipline
- Comprehensive education in mathematics, especially in discrete mathematics and one area of mathematical optimization (e.g. Mathematical Programming, Convex Optimization)
- Publications in leading conferences or journals are a strong plus at the entry level of a scientific career
- Curiosity and strong interest in rigorous methodological research
- Very good programming skills in C++
- Very good scientific writing skills in English. (Knowledge of German is not required for this position).

Salary level: TV-L E13, 100%

Application documents: CV, degree certificates, transcript of records (preferably as a single PDF file)

Website: https://mlcv.inf.tu-dresden.de/

Contact: mlcv@tu-dresden.de

At TU Dresden, the Chair of Machine Learning for Computer Vision offers a position for a

PhD Student Machine Learning

Tasks:
- Curiosity-driven basic research of fundamental mathematical optimization problems in the field of machine learning
- Design and analysis of algorithms for solving these problems, exactly or approximatively
- Implementation, empirical analysis and comparison of these algorithms with respect to real data
- Publication of findings and insights in internationally leading conferences and journals
- Teaching assistance, esp. co-supervision of student research projects, and tutoring, in English.

Requirements:
- A very good university degree in mathematics or computer science or a related discipline
- Comprehensive education in mathematics, especially in discrete mathematics and one area of mathematical optimization (e.g. Mathematical Programming, Convex Optimization)
- Publications in leading conferences or journals are a strong plus at the entry level of a scientific career
- Curiosity and strong interest in rigorous methodological research
- Very good programming skills in C++
- Very good scientific writing skills in English. (Knowledge of German is not required for this position).

Salary level: TV-L E13, 100%

Application documents: CV, degree certificates, transcript of records (preferably as a single PDF file)

Website: https://mlcv.inf.tu-dresden.de/

Contact: mlcv@tu-dresden.de

Founded by Dr.Yuanqing LIN in November 2017, AiBee--https://aibee.com/en/ is a leading AI startup providing AI total solutions, and its mission has been to empower and upgrade vertical industries with AI. We are a leading company in the application of AI technologies for retail and have developed full AI solutions for offline retailers that allow closing the loop among data, algorithms and product/service. By deploying the most advanced and innovative AI technologies (computer vision, speech recognition, natural language understanding, big data analytics, robotics, etc.), AiBee has grown into a strategic partner of many of the world’s largest retail chains.

We are looking for top-notch research interns from all levels (BS, MS, and Ph.D.) to join our Silicon Valley labs. We have access to a huge amount of real-wold data from large retail chains, enabling researchers like you to develop techniques at scale. Interns will have the opportunity to pursue interests across academic, applied research and engineering and will be exposed to problems across various domains in computer vision and machine learning such as:
• Object Detection, Segmentation, and Classification
• Pose Estimation and Tracking
• Activity Recognition
• Re-identification
• SLAM

In this internship, you will:
• Define ambitious, relevant research problems and criteria for evaluating success.
• Based on the project, help analyze and improve efficiency, scalability, and stability of corresponding deployed algorithms
• Build state-of-the-art solutions by designing algorithms and carrying out experiments.
• Have the opportunity to publish at top-tier conferences and/or journals such as CVPR, ECCV, ICCV, NeurIPS, etc…
• Work and collaborate with a world-class group of researchers and engineers led by chief scientist Prof. Silvio Savarese

Preferred Qualifications:
• Ph.D., MS or BS students in Computer Science, computer vision, machine learning related field.
• Ability to communicate complex research in a clear, precise, and actionable manner
• Experience working with deep learning frameworks and related tools in computer vision.
• Proficient in C++ or Python, or equivalent languages.
• If Ph.D. student, track record of publications at top-tier conferences such as CVPR, ECCV, ICCV, ICML or similar is preferred

To apply: please contact Prof. Silvio Savarese (aibee.usteam@gmail.com) with your resume and clarify your preferred start date.

AI and Image Analysis Group @ German Center for Neurodegenerative Diseases

We are looking for a Postdoc in Deep Learning for Medical Image Computing to join the research group of Prof. Martin Reuter at the German Center for Neurodegenerative Diseases (DZNE) in Bonn, Germany. The DZNE is among the top 10 institutions in Alzheimer’s Disease Research wold-wide, and among the top three with respect to citations & collaborations (Elsevier Report 2019). You will develop new research directions, building upon our ongoing research on machine learning methods for MRI analysis, MRI reconstruction, brain segmentation, registration, retinal OCT analysis, motion estimation, and geometry based shape analysis.

We offer:

• NETWORK: An interdisciplinary team of researchers, with strong collaboration ties locally (clinics, machine learners, population scientists) as well as internationally (Harvard Medical School, MIT, U Madison …). E.g. the PI Martin Reuter holds a faculty appointment at Harvard Medical School.
• COMPUTE: We work with the newest deep learning hardware. Two servers with each 8 NVidia V100 cards (nv-linked) are available just for our lab - plus a shared state-of-the art HPC cluster.
• DATA: The DZNE collects high-quality data in clinical and population studies. E.g. the DZNE Rhineland Study is a deeply phenotyped population study with already thousands of participants (aiming at 30K) and high-quality MRI, OCT images, MR-motion tracker data, genetics etc.. Manual labels, diagnosis, and QC ratings are prepared by experts.
• LIFE: Live in a city with one of the highest quality of life ratings! Bonn, the former capital of Germany at the Rhine river, has a large international community, great recreational activities, and the Cologne metro-area right around the corner.

Requirements include:

• Passion for research on deep learning for medical imaging.
• PhD in computer science, medical imaging, mathematics, physics, electrical engineering or a related discipline.
• Advanced knowledge of machine learning and deep learning (publications).
• Advanced skills in Python and PyTorch (or Tensorflow).
• Experience in working with medical imaging data is a big plus.
• Excellent written and verbal English communication skills (working language is English).

Responsibilities will include:

• Developing novel machine learning methods for medical imaging.
• Collaborating with other research scientists, clinicians, faculty members, postdocs locally and internationally.
• Supervising students.

Timeline, Salary, and Benefits

Please apply no later than 2/09

We expect the appointed candidate to start during spring of 2020. The initial appointment will be for two years, with the potential to renew further, depending on mutual agreement. We offer a competitive salary and benefits package (salary level E13 TV-L Federal tariff). We welcome both domestic and international applicants.

To Apply Please contact Martin.Reuter(at)dzne.de (email subject “MIC-PD-20”). We are looking forward to reading your application including your CV, contact information of two referees, a brief statement describing your personal qualifications and future research interests (up to 1 page), and a list of publications highlighting up to three most important ones (if possible in a single PDF file). Please ask if you have any questions. We look forward to hearing from you!

• Developing novel machine learning methods for medical imaging.
• Collaborating with other research scientists, clinicians, faculty members, postdocs locally and internationally.
• Supervising students.

Company Description:

Joining Intuitive Surgical, Inc. means joining a team dedicated to using technology to benefit patients by improving surgical efficacy and decreasing surgical invasiveness, with patient safety as our highest priority.

Eligibility:

Must be concurrently enrolled and returning to an academic program in the fall in an accredited degree-seeking program.

Primary Function of Position:

The candidate will work with a top-notch multi-disciplinary R&D team to develop medical imaging, surgical planning and navigation software on a new robotic surgical platform (video). 

We are seeking a talented individual to research and develop algorithms for medical computer vision and medical image segmentation. Expected contributions include literature survey, algorithm design and implementation, testing on a large dataset with ground truth. 

Roles and Responsibilities:

• Experiment with different machine learning models
• Develop algorithm prototype and evaluate on evaluation datasets
• Draft report and presentation

Skills, Experience, Education, & Training:

• A passion for developing technologies to improve the lives of hundreds of thousands of people.
• Self-motivated, self-disciplined and ability to work independently.
• Ability to perform fast prototyping and testing iterations and thinking outside the box to solve practical problems.
• Advanced MS or PhD student in the area of Computer Vision, Medical Image Analysis or Machine Learning.
• Solid knowledge and/or experience in one or more of the following areas is highly desired: 1) geometric computer vision: SLAM, SfM, pose estimation, 2) image segmentation, 3) machine learning / deep learning.
• Proficiency with Python and/or C++ to produce quick prototype and high quality code.
• Familiarity with standard computer vision, medical image processing and/or machine/deep learning packages.

Learning Outcomes:

• Applying knowledge/skill to make some real world impact
• Gain hands-on experience on medical computer vision and/or using Deep Learning on 3d medical image segmentation
• Gain experience of R&D in a product focused company
• Exposure to the discipline of project planning and management

Commitment:  Must be available to work full-time hours, M-F for 10-12 weeks beginning Summer of 2020.  

We are an AA/EEO/Veterans/Disabled employer.

To Apply: Apply online or send resume to tao.zhao@intusurg.com

Dr. Hakan Bilen is seeking creative and motivated postdoc candidates to work in Visual Computing Group in the topic of multi-task learning in computer vision. PhD in Computer Vision, Machine Learning, or closely related area and strong publication record at top computer vision and/or machine learning conferences (CVPR, ICCV, ECCV, NIPS, ICML, ICLR) and journals (PAMI, IJCV) are essential.

Please e-mail hbilen@ed.ac.uk your CV with the full publication list with the title [Prospective Postdoc] before Jan 24th 2020. The start date is flexible, the position is available from March 1st 2020 for a year with the possibility of extension.

PAII Inc. or Ping An Technology US Research Labs (located at North Bethesda, Maryland, USA) is one of the core research arms by Ping An Technology and Ping An Insurance Group, ranked 29# in the 2019 global fortune list. The lab mission is developing "clinician lead technology powered novel and effective clinical workflows" to improve patient care quality without increasing cost. The technology focuses are deep learning, medical image analysis and large-scale clinical informatics in the domains of quantitative imaging, precision medicine and preventive medicine. We commit to create an R&D environment where top-tier computer scientists and world-class clinicians can seamlessly collaborate and work together to tackle human health problems. We believe that is the best organic way of moving health forward and we have established in-depth main partnerships with several world leading hospitals and beyond.

We currently have close engagement with four world class clinical centers and a good range of 8~10 core projects covering emergency medicine, preventive rheumatology quantitative imaging, and more heavily on a comprehensive list of precision oncology imaging AI (e.g., liver, pancreas, thorax, OPX, etc.) problems. In 2019, we have contributed to 20+ patents and 10+ top tier publications in MICCAI/RSNA/CVPR/TMI, etc. One of our papers has been invited for MICCAI 2019 MedIA special issue. Recently we have submitted quite several papers to CVPR 2020, all targeted on advanced medical imaging and clinical informatics problems (our 2019 interns contributed approximately half of submissions). 

Job Duties: Conducting the state-of-the-art research and development to enable novel clinical applications at the intersection of medical Imaging, clinical informatics, statistical/deep learning. Details include 1) comprehending recent scientific and clinical literature, 2) collaborating with clinicians to form the proposal and ideas on improving a particular problem in preventive emergency medicine, precison rheumatology quantification, and deep learning and information fusion for multimodal oncology imaging, 3) implementing computer codes of algorithms to process, parse and analyze medical imaging data, 4) write inventions, patents and scientific papers.  

Qualifications: Candidates should be enrolled PhD students in good standing, in the programs of Computer Science, Electrical Engineering, Biomedical Engineers, or other related fields. Relevant and strong research experience in Deep Learning, Computer Vision, Image Processing (e.g., Detection/Segmentation/Registration/Recognition/Tagging, etc.) are desirable. Direct exerience on medical imaging is a plus but not a must. We solve real world problems with high clinical/techolgical impacts. Hands-on coding skills via deep learning toolkits, such as PyTorch, Tensorflow and strong analytical ability are required. 12 weeks (longer term more preferred) are minimal.

Application Procedure: please contact Dr. Le Lu (www.cs.jhu.edu/~lelu) who serves the lab director. www.paii-labs.com Please contact Dr. Le Lu with your brief introduction and a detailed resume, at email_1 or email_2 

Salary: salary grade E 13 TV-L

Post Summary: The Remote Sensing Image Analysis (RSiM) group at the Faculty of Electrical Engineering and Computer Science, Technische Universität Berlin, Germany is looking for highly motivated PhD candidates. The research of the PhD candidates will aim at developing innovative machine learning techniques (with a special focus on deep learning) for the analysis of big data from space. The main topics include: 1) developing deep neural network models that can overcome the data imbalance problems for satellite image classification; and 2) developing active learning methods that are applicable to the designed deep neural networks.

Qualifications: MSc degree is required in computer engineering or computer science with experience in computer vision, deep learning for image understanding. Very good command of German and English is required.

Application Procedure: For more information visit https://tub.stellenticket.de/en/offers/74416/

Salary: salary grade E 13 TV-L

Post Summary: The Remote Sensing Image Analysis (RSiM) group at the Faculty of Electrical Engineering and Computer Science, Technische Universität Berlin, Germany is looking for highly motivated PhD candidates. The research of the PhD candidates will aim at developing innovative machine learning techniques (with a special focus on deep learning) for the analysis of big data from space. The main topics include: 1) developing deep neural network models that can overcome the data imbalance problems for satellite image classification; and 2) developing active learning methods that are applicable to the designed deep neural networks. 

Qualifications: MSc degree is required in computer engineering or computer science with experience in computer vision, deep learning for image understanding. Very good command of German and English is required.

Application Procedure: For more information visit https://tub.stellenticket.de/en/offers/74416/

Salary: Appointment will be made on the SFI Post-Doctoral Researcher Level Scale (based on candidates experience) at a point in line with Irish Government Pay Policy.

Post Summary: The ADAPT Centre, the centre for digital content technology, seeks to appoint a Postdoctoral Research Fellow to conduct research in the area of computer vision and image processing in our Industry facing research team ‘Spokes’. We require a highly motivated researcher to join the team in Trinity College Dublin in the school of Computer Science and Statistics to work in collaboration with industry in an exciting programme of applied research. The candidate should have a mature personal research plan in at least one of the relevant following areas: object detection, recognition and segmentation in image data.

Qualifications:Candidates must have a PhD in computer science, statistics or related fields with 4 to 10 years research experience (including PhD studies).

Knowledge & Experience (Essential):

• Research experience in machine and deep learning for image processing and computer vision or similar areas including 3D point cloud, pattern detection, recognition and geo-location(Essential)

• Publications in the top conferences (e.g. ICML, CVPR, ICCV) and/or journals (e.g. IEEE Trans. Image Processing, Pattern Analysis and Machine Intelligence, International Journal on Computer Vision) (Essential)

• Excellent programming skills (e.g. C++, python) with experience using deep learning libraries (e.g. caffe, torch, theano etc.) (Essential)

Application Procedure:

Candidates should submit a cover letter together with a full curriculum vitae including the names and contact details of 3 referees 

(email addresses if possible) to:

Name: Monica Lechea

Dr. Boult and his team at UCCS are seeking highly motivated postdoctoral researchers with a strong record of accomplishment in machine learning and computer vision, ideally with incremental learning, deep learning, or open-set learning. Classic machine learning and AI make a closed-world assumption, leading to fragile systems that cannot label novel inputs as unknown nor handle novel variations in the world. Very few existing systems can detect novelty and then learn from previous unknowns – almost all systems misclassify the unknown. At the core of intelligence is the ability to recognize when we do not know something, analyze the need to learn about it, and then, when needed, to adapt and learn it – a process we call open-world learning. We seek a candidate to join our multi-institution efforts exploring four main research directions: 1) Formalized models for open world learning with extreme-value theory, 2) Semi-supervised and unsupervised incremental learning 3) Open world learning for object classification and detection, and 4) Open world learning in visual observation of games. The PostDocs are expected to both do research, develop software, write papers, and lead/works with students. Five or more years of Computer vision and/or Machine Learning research and development experience required. Developments will be in Python and C++ on Linux and significant systems/software engineering experience in one or both languages preferred. A Ph.D. is preferred but an MS with significant experience will be considered. International candidates with strong English skills will be considered; we can manage the visa issues. The University of Colorado is an equal opportunity employer; women and underrepresented populations are strongly encouraged to apply. We are expecting to fill two positions to start ASAP 2019, contingent on the project funding.   You can apply at You can apply at https://cu.taleo.net/careerse ction/2/jobdetail.ftl?job=17908&lang=en

The School of Computer Science and Electronic Engineering at the University of Essex is a large and dynamic department in the Faculty of Science and Health. The School is internationally known for its research in a range of areas and offers excellent education to its students and is now seeking to make two appointments at Research Officer and/or Senior Research Officer level.

You will support the Embedded and Intelligent Systems Laboratory's work on computer/robot vision systems in the School of Computer Science and Electronic Engineering, as part of the recently awarded RICE Project funded by the EPSRC National Centre for Nuclear Robotics Flexible Partnership Fund. The RICE project brings together National Centre for Nuclear Robotics (University of Essex), Australian Centre for Robotic Vision (Queensland University of Technology, Australia), and University of Nevada (Reno, USA) for groundbreaking research in the area of visual place recognition for robotics in extreme environments, more specifically underground mining and nuclear decommissioning. It is a dedicated research programme combined with networking activities, including short-term and longer exchange visits of researchers and student placements.  
 

The specific focus of the post is to aid in the production of the deliverables associated with the RICE Project in conjunction with our partners, the Australian Centre for Robotic Vision (Queensland University of Technology), and University of Nevada (Reno). The project will address the specific research needed for the challenging problem of robust vision to develop robotic vision algorithms to enable robots to perceive their environments and consequently act purposefully under the incredible range of environmental conditions possible, including low light, rain, snow, ice sleet, fog, smoke, dust, wind, glare and heat. You will get a chance to work closely with Prof Michael Milford, Prof Kostas Alexis, Prof Klaus McDonald-Maier and Dr Shoaib Ehsan on the RICE project.

Position:

The Vanderbilt University Medical Center (VUMC) in Nashville, Tennessee is seeking motivated post-doctoral and other academically bound candidates to develop their translational research career in imaging of cutaneous manifestations of cancer and its treatments. Trainees in this well-funded program will enjoy a competitive salary, benefits, and ample resources to advance their career and research. Initial appointment will be for one year with annual renewal options. Multimodal dermatologic imaging techniques including 3D photography, hyperspectral imaging, and confocal microscopy, coupled to image analysis techniques including deep learning neural networks, will be applied in ongoing multicenter clinical trials and basic science research.

Environment:

Candidates will benefit from a personalized research program catered to their goals utilizing resources and mentoring within the Vanderbilt-Ingram Cancer Center (Madan Jagasia), Dermatology (Eric Tkaczyk), Computer Science (Benoit Dawant) and the Biophotonics Center within Biomedical Engineering (Anita Mahadevan-Jansen). This environment brings together clinicians, basic scientists, engineers and statisticians in close collaboration due to its interdisciplinary research and close physical proximity of the School of Medicine to the School of Engineering (100-200 yards).  Example publication: https://www.nature.com/articles/s41409-018-0211-8

Qualifications:

All positions require a B.S. degree.  Post-doc fellows should have a Ph.D. or M.D. with expertise in at least one of the following: clinical translational research, computer science, dermatologic imaging, multivariate data analysis, image processing, optics, clinical device validation, clinical trials and study design, immunology, or biomarkers. The Vanderbilt University Medical Center is an equal opportunities employer.

Application and contact:

Interested applicants are requested to mail their CV, a one-page personal statement, and two letters of recommendation with reference phone numbers and email addresses to: