Postdoctoral Training Opportunity - Computer Science/Statistics/Applied Math - Machine Learning
The Northwestern University Argonne Institute for Science and Engineering (NAISE) is looking for a motivated and talented postdoctoral trainee to explore computer vision, artificial intelligence and machine learning (ML). Supervised learning approaches require a significant amount of “labeled data”. They seek a candidate to explore lots of CV/ML such as: 1) computer vision pre- and post- processing for ML, 2) computer vision- based approaches to assist in labeling, and/or 3) edge to HPC (approaches for movement of compute and data between the edge and HPC).
The successful candidate will be working in a diverse and multidisciplinary team as part of the Sage CyberInfrastructure project that aims to underpin the nation's science infrastructure with state-of-the-art edge computing and intelligence fabric.
- Teamwork, the ability to work in large teams and tackle hard problems in a distributed version control environment
- Ability to work on interdisciplinary teams with domain scientists
- Computer science/applied math or statistics skills. Skills in advance analytical techniques such as ML/AI, computer vision, optimization. Either experience in or the ability to be able to learn (quickly) AI/ML frameworks such as Tensorflow or PyTorch
- Natural curiosity.
- Adherence to excellent coding practice: Self documenting code, testing, git, GitHub, CI platforms (Travis, appveyor etc).
- Skill in dockerizing applications, scheduling, kubernetes etc.
- Experience with HPC or cloud computing.
Interested candidates should send a CV and cover letter indicating the position for which they would like to be considered to Nicola Ferrier email@example.com by December 1, 2020 to ensure consideration. They will continue to review applications until the position is filled.
Northwestern University is an Equal Opportunity, Affirmative Action Employer of all protected classes, including veterans and individuals with disabilities. Women, racial and ethnic minorities, individuals with disabilities, and veterans are encouraged to apply. Hiring is contingent upon eligibility to work in the United States.