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with tensor networks, AI in physics and materials, etc.). A Ph.D. in Physics or a closely related field is required. The initial appointment will be for one year, and is renewable for another one or two
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development reviews, leadership and entrepreneurship training, collaborative training opportunities, and networking and conferences. Qualifications: PhD in Molecular Biology, RNA Biology, Biophysics, or a
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analysis methods, including quantitative structural analysis, network-based functional analysis, voxelwise cross-modality analyses, graph theoretic approaches, and machine-learning based applications
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a robust academic and professional network, preparing for leadership roles in academia, policy, or industry. Receive the IT support required by their research (e.g. specialized software or computation
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independence, long-term career advancement, and the development of an intramural and extramural academic network tailored to the candidate’s interests. This fellowship will allow candidates to develop, or expand
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multiple NIH grants, including the NIH Human Immunology Project Consortium (HIPC), a highly collaborative national network that the successful candidate will join. Available areas of research include both
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opportunities at Yale. This includes seminars from internationally renowned researchers and ‘Meet the Speaker’ lunches, and professional development and networking activities including via the Yale Postdoctoral
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the direction and supervision of Prof. Lucila Ohno-Machado, we seek to appoint full-time Postdoctoral Associates (two positions) in the areas of privacy-preserving health data sharing, artificial neural network
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Postdoctoral Associate in Computational Neuroscience at Yale The Post-Doctoral Associate will develop predictive, gene-regulatory networks linked to Parkinson’s and other neurological diseases in
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-on experience in blockchain technology (preferably Ethereum) and/or machine learning. Solid foundation in computer network and/or data analysis. Strong programming skills, preferably in Java. Ability to work