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of Computation Group, seeks applicants for a postdoctoral fellowship to conduct research in differentially private learning, its connections to replicability of algorithms, and algorithmic fairness. Basic
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University of California San Francisco | San Francisco, California | United States | about 2 hours ago
: 88307BR The Cardiovascular Genetics Center at University of California, San Francisco is seeking an experienced bioinfomatician to faciliate several lines of research that relate broadly to inherited forms
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biology, genetics, or a closely related quantitative field. A degree in computer science is especially valuable due to the software engineering, algorithmic, and AI/ML components central to this role
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The Associate in Research will be responsible for using and developing computational algorithms to analyze single-cell and spatial-omics datasets. Specifically, we have multiple projects where we are generating
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General Summary of the Position Postdoctoral positions in Deep-Learning Omics are available in the Zhou Lab (https://profiles.umassmed.edu/display/20062865 ). The Zhou Lab at UMass Chan Medical
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Perrimon’s group in the Program of Genetics at Harvard Medical School. Perrimon lab is actively generating data sets of omics scale and this position will involve working with other post-doc trainees in
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, behavioral, clinical, genetic, and proteomic data. Prepares documentation of existing and newly developed brain image analysis pipelines, algorithms, and quantitative methods. Assists the team leader in
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Sequencing samples from the UKBiobank. The project aims at the wide-spectrum prediction of human phenotypes, unlocking new frontiers in clinical genetics, precision medicine, disease risk prediction, and
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in particular in human. The MDM team is collaborating a lot with the bioinformatic hub to make our prediction accessible to the public. The MDM lab is part of the Genome and Genetic department, also
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science. The successful candidate will develop innovative methods and models to decode the language of the genome and advance our understanding of how genetic variation contributes to complex diseases