Postdoctoral Fellow - Lehigh University

Requisition #: A-114580-37

Status: Full Time

Type: Other

School: Whiting School of Engineering

Department/Program: Department of Applied Mathematics & Statistics

Location City: Bethlehem

Location State: PA

Location Zip Code: 18015

Closing Date: Open until filled

General Description

Postdoctoral Fellow - Lehigh University

We invite applications for a unique cross-institution Postdoctoral Fellowship position that is available immediately.  The candidate will have co-primary supervisors Prof. Daniel P. Robinson and Prof. René Vidal. The initial appointment will be at Robinson's lab for one year, with a second year at Vidal's lab that is contingent on a satisfactory first year. Opportunities for collaboration include the Foundations and Applications of Mathematical Optimization and Data Science (MODS) group at Lehigh University and the Collaboration on the Mathematical Foundations of Deep Learning (THEORINET) at The Johns Hopkins University and The University of Pennsylvania, among other institutions.

About Lehigh University: Founded in 1865, Lehigh University combines outstanding academic and learning opportunities with leadership in fostering innovative research. Recognized among the nation's highly ranked research universities, Lehigh offers a rigorous academic community for over 5,000 undergraduates, 2,000 graduate students, and about 550 full-time faculty members. Lehigh University is located in Bethlehem, PA., a vibrant and historic area. Over 820,000 people live in the Lehigh Valley, which is in close proximity to New York City and Philadelphia. Lehigh has five colleges, including the new College of Health, and is investing substantially in new innovative research and academic programs to enhance its intellectual footprint. These investments, based on faculty-driven initiatives, will advance the University's commitment to scholarship and to the student experience.

Equal Employment Opportunity: Lehigh University is an affirmative action/equal opportunity employers that does not discriminate on the basis of age, color, disability, gender identity or expression, genetic information, marital or familial status, national or ethnic origin, race, religion, sex, sexual orientation, or veteran status.

Qualifications

Candidates must have completed a Ph.D. in applied mathematics, computer science, electrical engineering, statistics or a closely related field prior to their appointment start date and show definite promise in research. The successful candidate will be expected to collaborate with Prof. Robinson and Prof. Vidal on problems related to optimization and machine learning, such as deep subspace clustering, and their applications in computer vision. Therefore, a strong background in machine learning, optimization and statistics is required, and knowledge in computer vision would be beneficial.

Application Instructions

Review of applications will begin immediately and will continue until the position is filled.  Applicants are asked to submit to the following items: (a) a cover letter (b) a curriculum vita; (c) a description of current and past research (1-3 pages); (d) a plan for future research, and (e) three letters of recommendation.

To apply for this position, visit: apply.interfolio.com/114580

The Johns Hopkins University is committed to equal opportunity for its faculty, staff, and students. To that end, the university does not discriminate on the basis of sex, gender, marital status, pregnancy, race, color, ethnicity, national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status or other legally protected characteristic. The university is committed to providing qualified individuals access to all academic and employment programs, benefits and activities on the basis of demonstrated ability, performance and merit without regard to personal factors that are irrelevant to the program involved.

Pre-Employment Information

The successful candidate(s) for this position will be subject to a pre-employment background check.

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