25 big-data-and-machine-learning-phd Postdoctoral positions at University of Cambridge
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include a motivation statement, which demonstrates how their research interests and expertise relate to the project and the desired tasks. Applicants must hold a PhD in a relevant specialist subject (e.g
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PhD in a relevant specialist subject (e.g., Latin language and/or literature, medieval studies, cultural studies, history, liturgy, or theology) or have evidence that the PhD will be completed by
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research skills, provide instruction or plan/ deliver seminars relating to the research area. The successful candidates will have a PhD (or expect to soon be awarded) in the physical or biological sciences
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research skills, and deliver seminars relating to the research area. The successful candidate should possess a PhD in Applied Analysis of Geophysical Fluid Models. Limit of tenure: 1 year in the first
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and Innovation Associate to join this ambitious project. You should hold a PhD in a relevant field such as applied/pure mathematics or physics and have an established track record of original research
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://degradationproject.com/ ) and NEXGENNa (http://nexgenna.org/ ) projects and participation in regular relevant FI meetings. Applicants should hold (or be about to obtain) a PhD in Chemistry, Materials Science, or a closely
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. The research undertaken includes the interpretation of collider data and theory support for LHC phenomenology and future colliders. The Research Associate will be working on beyond the Standard Model
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candidate should have (or expect to soon be awarded) a PhD in quantum information theory (including some aspects of quantum computing, quantum cryptography and/or quantum communication) and some experience in
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connectome, with a focus on the chemosensory circuits involved in human host-seeking. The principal focus will be on the high level proofreading, annotation and analysis of connectomics data. This will include
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of economics, programming in MATLAB and JULIA, and the Health and Retirement Study data is necessary. Understanding linkages with administrative medical records is also highly valuable. The successful candidate