VetJobs - The Leading Military Job Board

Postdoctoral Fellow - Mathematical Institute for Data Science

The Johns Hopkins University's Mathematical Institute for Data Science (MINDS) invites applicants for multiple positions as a Postdoctoral Fellow. Review of applications will begin on 1/1/2022. Candidates must have completed their Ph.D. prior to their appointment start date and show definite promise in research and teaching. The appointment is for one year, renewable for up to three years, with a typical duration of at least two years. Opportunities for collaboration include an NSF-Simons Collaboration on the Mathematical Foundations of Deep Learning (THEORINET), the NSF-TRIPODS Institute on the Foundations of Graph and Deep Learning, the DARPA GARD and DARPA RED programs, and ONR MURI on Control and Learning Enabled Verifiable Robust AI (CLEVR-AI), and an ARO MURI on Semantic Information for Multimodal Data.

The Mathematical Institute for Data Science has 35 faculty affiliated with primary appointments in the Departments of Applied Math & Statistics, Biomedical Engineering, Computer Science, and Electrical and Computer Engineering. MINDS faculty are supported by multiple grants, including an NSF-Simons Collaboration on the Mathematical Foundations of Deep Learning (THEORINET) and the NSF-TRIPODS Institute on the Foundations of Graph and Deep Learning. More information about the Mathematical Institute for Data Science can be found at https://www.minds.jhu.edu/.

The Whiting School of Engineering comprises over 200 full-time tenure-track, research, and teaching-track faculty in nine academic programs with a total annual research budget of over $100 million. Research partnerships with the Johns Hopkins School of Medicine, Applied Physics Laboratory, Bloomberg School of Public Health, and the Krieger School of Arts and Sciences make the Whiting School of Engineering a unique research and educational environment. Student enrollment exceeds 1800 at the undergraduate level with over 1000 full-time MS and PhD students. The Engineering for Professionals program enrolls over 2000 part-time continuing education students and is the largest program of its kind in the country.

The Johns Hopkins University is committed to active recruitment of a diverse body of researchers. The University is an Affirmative Action/Equal Opportunity Employer of women, minorities, protected veterans, and individuals with disabilities and encourages applications from these and other protected group members. Consistent with the University's goals of achieving excellence in all areas, we will assess the comprehensive qualifications of each applicant.

The successful candidate will be expected to collaborate with Prof. Vidal on problems that include:

1. Foundations of deep learning: learning and control, convergence and implicit bias in overparametrized models, non-convex optimization.

2. Adversarial and lifelong learning: principled defenses for images and videos, reverse engineering of attacks, min-max optimization, lifelong unsupervised learning.

3. Computer vision: scene interpretation, action recognition,

4. Biomedical data science: video-based diagnosis of autism and Tourette syndrome, cell detection and reconstruction. A strong background in machine learning, optimization, statistics, dynamical systems, computer vision, or biomedical data science is required.

Applicants are asked to submit (a) a cover letter, (b) a vita, and (c) a research statement (1-3 pages) to http://apply.interfolio.com/98000. In addition, the applicants should use Interfolio to request at least three letters of recommendations to be submitted directly by the recommenders.

Job Type: Full Time Johns Hopkins University is committed to active recruitment of a diverse faculty and student body. The University is an Affirmative Action/Equal Opportunity Employer of women, minorities, protected veterans and individuals with disabilities and encourages applications from these and other protected group members. Consistent with the University’s goals of achieving excellence in all areas, we will assess the comprehensive qualifications of each applicant.