63 post-doc-image-engineering-computer-vision Postdoctoral positions at Yale University
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, computer science, data science, social sciences, public policy, or a relevant interdisciplinary area. Interest in addressing the governance, ethical, legal, and societal implications (GELSI) posed by digital
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applications in python with PyTorch/Huggingface/SpaCy, applications of computer vision and signal processing in Tensorflow or PyTorch, Llama and GPT models. Essential Duties Develop and execute new and/or highly
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. Qualifications We are seeking candidates who meet the following criteria: A PhD or equivalent degree, already obtained, in a related field e.g., philosophy, law, computer science, data science, social sciences
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engineering is considered a plus. The lab has routine access to Krios and FIB-milling instruments. 2) Genome editing: Projects involve developing novel genome editing tools and optimizing in vivo delivery
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science, and biomedical and biological engineering. This position is funded by the T32 Training Program in the Department of Anesthesiology at Yale, and will provide mentorship on transition to research
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projects, we have access to large datasets including the Million Veteran Program and the Psychiatric Genomics Consortium. The ideal candidate should hold an MD or PhD, and have a strong background in human
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doctorate (PhD, or MD, or MD,PhD) degree in medicine or life sciences/biology is required. Prior experience working in animal models, animal surgery, molecular biology techniques such as cloning, cell culture
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CADMY is offering several Postdoctoral Associate positions designed for recent graduates of Ph.D. programs working at the intersection of AI, Game Theory, Economics, and Computer Science. We
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of mutational processes in human health and disease. We are an interdisciplinary team of experimental, computational, and clinician scientists allowing us to generate and analyse complex data from emerging
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(SUDs), psychiatric conditions, and other behavioral and lifestyle characteristics that impact human health using large datasets and biobanks including the Million Veteran Program (MVP), the SUD working