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federated learning. Current research projects aim to identify genetic variants/genes associated with disease traits (susceptibility/treatment response/progression) toward personalized medicine and unravel
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team has a strong focus on machine learning and interpretable deep learning. However, more theoretically oriented candidates, interested in developing mathematical and mechanistic models of the immune
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position with experience in physiologic signal processing (e.g., EEG) and statistical/machine learning methods. The applicant would be joining the lab of Dr. Jennifer A. Kim MD-PhD, which focuses
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Postdoc opportunity: machine learning methods for high-content image screens (Verhaak lab) Description The Verhaak lab is looking to recruit a postdoctoral associate who will help us develop
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settings You are comfortable in a multi-project lab with a dynamic young international environment YOUR MISSION Development in close collaboration with research staff working on cutting-edge deep learning
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, including working with qualitative and quantitative data Demonstrated ability (or potential to learn) to forge connections with community members Independence to lead a project as well as willingness to work
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Program, Million Veterans Program, and UK Biobank, either a single biobank or cross-biobanks using federated learning. Current research projects aim to identify genetic variants/genes associated with
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relevant areas, including but not limited to biomedical natural language processing, medical image analysis, or AI-assisted healthcare applications. Proficiency in programming, particularly in deep learning
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: combining machine learning and mechanistic modeling, multisimulation (interoperation with other tools), high-resolution simulations of subcellular chemical dynamics, and algorithm development (GPUs
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computing, machine learning methods, and or statistical genetics. The ideal candidate will also demonstrate: A high level of drive and initiative, and track record of impactful research outcomes Experience writing