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, Engineering or related field. A strong background/knowledge in machine learning and computer vision, natural language processing is a plus. Solid mathematics foundations, especially statistics, calculus and
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of functionalized chips. Reporting: Communicate findings to project partners with diverse backgrounds (e.g., space systems engineering, astrobiology, microfluidics) to support the development of a prototype LMCOOL
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, combustion processes, propulsion and flight physics, communication and networking, and computational and information sciences. About PHOTONICS, ELECTRONICS, & QUANTUM SCIENCES (PE&QS) Materials (and related
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, Integrated sensing/memory/logic materials, Synchrotron light source techniques, Machine-learned force field development, Technology computer-aided design, AI hardware accelerators, Augmented reality hardware
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: Letter of motivation and academic CV Organisational Unit Inverse problems and mathematical image processing is one of the research areas at the Department of Mathematics and Scientific Computing, which is
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/2025 Job Summary The Department of Sustainable Earth Systems Sciences (SESS) at The University of Texas at Dallas invites application for a Postdoctoral Scholar in the field of passive source seismology
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, and decision support. Qualifications Required: PhD in Computer Science or a related field, with a focus in databases, data systems, theory, or algorithms. Strong publication record in top-tier venues
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of British Columbia, Vancouver campus is seeking one postdoctoral fellow to join our dynamic team in the AI in Medicine Lab (www.aimlab.ca). This position is based in the School of Biomedical Engineering. The
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: The position requires a computer to include all Microsoft software, access to NCAA Applications, ARMS, Teamworks and other Cap Management software. In addition, the position requires the use of a cellular
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/Qualifications Computer operation (Word, Excel, Origin, EndNote, creating graphics, image processing), experimental data processing. Specific Requirements Basic knowledge of material characterization techniques