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(completed or near completion) in Computer Science, Computer Vision, NLP, Machine Learning, Computer Graphics/Animation, HCI, or a related field. Strong background in deep generative modelling (diffusion
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for candidates with a Ph.D. in economics, management, political economy, or related areas with expertise either in game theory, particularly mechanism design or experimental methods and machine learning. The term
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renewable for a second year pending budgetary approval. In addition, the research support, the position offers the opportunity to teach one 3-credit course per academic year designed to help undergraduate
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://postdoc.wustl.edu/prospective-postdocs-2/ . Trains under the supervision of a faculty mentor including (but not limited to): Learn to conduct brain imaging research with surface-based analyses methods and the HCP
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enable students to earn associate or bachelor’s degrees through a combination of in-person, online or blended learning. All of our system institutions place strong emphasis on service — helping to build
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have access to state-of-the-art technologies in multi-omics single-cell sequencing and Hi-D flow cytometry. The project focuses on the role of B cells, plasma cells, and (auto)antibody responses in
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vision and novel applications of machine learning. Advanced knowledge of R or Python is required. Intermediate knowledge in C/C++ and/or at least one SQL dialect is preferred. Apply online at https
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. MATLAB, C/C++, Python. Highly motivated and keen on working in an international and interdisciplinary team. Applicants with strong background in the following fields are preferred: Machine Learning Formal
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Interaction, Educational Technology, Learning Sciences, Cognitive Science, or a closely related field. Job Description: The University of Florida (UF) is accepting applications for a full-time OPS Postdoctoral
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motivated post-doctoral associate with a strong background in control systems and machine learning to join the research team of Prof. M. Umar B. Niazi. The position focuses on the development of digital twins