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: Exempt ---- Earliest Start Date: Immediately ---- Position Duration: Expected to Continue Until Aug 31, 2026 ---- Location: UT MAIN CAMPUS ---- Job Details: General Notes Planet Texas 2050 is a UT Austin
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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Job Posting Title: Postdoctoral Fellow, Texas Center for Pediatric and Congenital Heart Disease ---- Hiring Department: Department of Pediatrics ---- Position Open To: All Applicants ---- Weekly
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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Research Fellowship (PRF) for PhD CS Program Location Rio Grande Valley, Texas College College of Engineering and Computer Science Department College of Engineering and Computer Science / Computer Science
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, ethical research standards, and applicable federal and state regulations ELIGIBILITY REQUIREMENTS Individuals with a PhD degree in computational biology, bioinformatics, data science or a related field are
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involve algorithm development, simulation, test rig set-up, and experimental validation. Job Requirements: The candidate must at least have a PhD Degree in Mechanical Engineering, Automation, Control
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Responsibilities: The successful applicant will be responsible for: Obtaining theoretical results at the interface of geometry and biophysics Designing, implementing, and testing algorithms to model active matter
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planning algorithms for GPS-denied lunar environments and extreme operational conditions stochastic optimisation frameworks for mission-critical decision-making under uncertainty Research areas and technical
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application to lineage tracing Algorithms for characterizing structural alterations in bulk and single cell whole-genome data Mutational signature analysis for cancer/brain samples Analysis of repetitive