Postdoc position at SISL in Optimization and Stochastic Programming
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 which apply advanced signal and information processing techniques to problems in acoustic modeling and detection, classification, and tracking using both active and passive underwater sonar systems.
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 underwater acoustics, target tracking, or signal processing are preferred, but all candidates are encouraged to apply. A familiarity with mathematical statistics, probability theory, and computer programming is desirable but not essential. The successful applicant should demonstrate strong potential as an independent researcher and small (2-5 people) 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.
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.
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.