72 parallel-processing-bioinformatics positions at Yale University in computer-science
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disease (Braun, Cancer Cell, 2021) in kidney cancer. The ideal candidate will have a strong background in computer/data science (including statistics), knowledge of R and python, and experience with high
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Yale Analog and RF Circuits and Systems (ARCS) Research Group, Department of Electrical and Computer Engineering, Yale University The Analog and RF Circuits and Systems Research Group in
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genomics, multiomic integration, statistical modeling, or machine learning is desirable but not required. Candidates from computational biology, bioinformatics, computer science, statistics, applied
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, bioinformatics, computer science, statistics, applied mathematics, physics, bioengineering, immunology, or related fields are encouraged to apply. The position offers opportunities to publish methodological and
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recognize that artificial intelligence and machine learning are changing all aspects of neuroscience from analysis of neural activity to network modeling to imaging to bioinformatics to molecular modeling. We
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spatial omics, longitudinal biomarkers, computer vision, electronic health data) with cutting-edge AI, we aim to fundamentally transform Parkinson’s disease from a disease without cures into a predictable
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, retinal diseases, and vision science. Training opportunities may include imaging analysis, bioinformatics, statistical analysis, and grant and manuscript development. The specific training plan will be
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these questions and advance novel therapeutics for infertility. The candidate will use bioinformatic and computational tools to analyze single-cell and spatial transcriptomic data. Your work will be central to
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through peer-reviewed publications. Qualifications Candidates should possess: Ph.D. in Bioinformatics, Computational Biology, Computer Science, Genetics, Molecular Biology, or a related discipline. Strong
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conferences, and through peer-reviewed publications. Qualifications Candidates should possess: Ph.D., completed or expected, in Bioinformatics, Computer Science, Statistics, Computational Biology, Biomedical