SISL Postdoctural Fellowship, Machine Learning job description

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Postdoc position at SISL in Optimization and Stochastic Programming

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Fellowship Description

The Signal and Information Sciences Laboratory (SISL) of the Applied Research Laboratories, The University of Texas at Austin (ARL:UT) wishes to invite applications for one or more postdoctoral fellowship positions. SISL is currently involved in a variety of exciting research programs in both traditional machine learning (ML) and modern deep learning applied to both active and passive underwater sonar systems. SISL is currently in the early stages of developing deep learning approaches to characterize complex, incompletely labelled acoustic data sets and to perform multiclass classification on time series data, tracks, and various image representations of acoustic data.

Applicants should have a recent Ph.D. in physics, math, engineering, or other related applied sciences. Applicant must have received his or her Ph.D. within the last three years in order to be eligible. Individuals with research experience in ML, artificial intelligence (AI), and computer programming are preferred, but all candidates are encouraged to apply. A familiarity with probability and statistics, underwater acoustics, or signal processing is desirable but not essential. The successful applicant should demonstrate strong potential as an independent researcher and small team collaborator.

The appointment is contingent upon the completion of the requirements for a Ph.D. and will be for an initial period of one year with the possibility of renewal for an additional year. Outstanding recipients may be considered for staff positions at the completion of their appointment. U.S. citizenship is required. All positions are security sensitive and a background investigation will be conducted.

Salary Range: determined by experience and qualifications. Excellent fringe benefits.

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How to apply

Candidates should submit a curriculum vitae (with citizenship indicated), publication bibliography, three letters of reference, and a copy of two recent papers or manuscripts to:

Jason Aughenbaugh, Ph.D.
jason@arlut.utexas.edu
Signal & Information Sciences Laboratory
Applied Research Laboratories
The University of Texas at Austin
P.O. Box 8029
Austin, TX 78713-8029

The University of Texas is an affirmative action equal opportunity employer.