59 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at The University of Arizona
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on semiconductor devices for next-generation computing, including quantum emitters and neuromorphic transistors. The ideal candidate should have a strong background in solid-state physics, electronic materials
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) bi-metallic alloys, specifically under cyclic loading. This is a year-to-year appointment, contingent upon funding and performance. Outstanding U of A benefits include health, dental, vision, and life
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projects in AI-driven GNC for space robotics systems, leveraging both classical optimization techniques and modern machine learning methods. Lead and support research projects in AI-driven solutions for SDA
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research projects in AI-driven GNC for space robotics systems, leveraging both classical optimization techniques and modern machine learning methods. Lead and support research projects in AI-driven solutions
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related field. Preferred Qualifications Experience with spatiotemporal analysis using R, Python, and/or comparable computer programming languages. Experience in high performance computing. Experiencing
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work will focus on problems in controls, machine learning, image reconstruction, wavefront sensing, and instrument development and test. As time permits, you will be encouraged to conduct your own
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date. Outstanding UA benefits include health, dental, vision, and life insurance; paid vacation, sick leave, and holidays; UA/ASU/NAU tuition reduction for the employee and qualified family members
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the forefront of understanding drug disposition alterations in liver disease. Outstanding UA benefits include health, dental, vision, and life insurance; paid vacation, sick leave, and holidays; UA/ASU/NAU
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/2028. Outstanding UA benefits include health, dental, vision, and life insurance; paid vacation, sick leave, and holidays; UA/ASU/NAU tuition reduction for the employee and qualified family members
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Qualifications PhD or MD, PhD degree in neurobiology, biophysics, molecular biology, biochemistry or related field of study. Preferred Qualifications Experience with computational fluid dynamics. Experience with