34 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:" Fellowship positions at University of Michigan
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research projects in computer vision, machine learning, AI, and robotics. Projects may include physically-grounded AI guidance agents, modeling of multimodal data, and generative AI systems for situated
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automation, computational drug design, machine learning, and software engineering. The ideal candidate will contribute to innovative research and the development of advanced computational tools within our lab
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behaving mice, and advanced modeling + machine learning analyses. Please read more about our research at www.apostolideslab.org . Key questions we want to answer are: How do neural circuits extract
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conditions and policy outcomes. Desired areas of expertise include: dynamic and complex systems, agent-based modeling, computer programming (familiarity with R, Python, Netlogo), statistical analysis
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) in addition to Medicare and Medicaid claims. Our team also has extensive methodologic experience, including natural experiments/econometrics and various machine learning techniques. The Fellow will
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, machine learning and AI-based computational tools to advance biomedical as well as oncology research. The fellow will work under the supervision of Dr. Veera Baladandayuthapani and there will be
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. Experience working with medical images. Very good computer programming skills and physics background is essential. Desired Qualifications* Nuclear medicine imaging/dosimetry experience. Experience in image
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of design and fabrication of medical devices, 3D printing, microfluidics, mechanics of materials, biomaterials, blood-material interactions, computer aided design, and/or in vitro/in vivo evaluation
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subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work modes . Background Screening Michigan Medicine conducts background screening and pre
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at the discretion of the hiring department. Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work