99 parallel-programming "Intelligent Systems Group" Postdoctoral research jobs at Yale University
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related to the conduct of human based research, a valuable skill when working with clinical data. . The above training will provide essential training in systems and software engineering. Mentorship
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Show all breadcrumbs Postdoctoral Opportunity – Kim Lab/ Translational Systems Cancer Biology – Yale School of Medicine Thursday, April 2, 2026 Overview of Lab/Department: The Kim Lab in the
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Show all breadcrumbs Postgraduate Associate (Garg Lab – Heterogeneity In Cell Systems) Yale School of Medicine Tuesday, February 17, 2026 We seek motivated and enthusiastic individuals to join the
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Show all breadcrumbs Postgraduate Research Associate Position in Molecular, Cellular, and Developmental Biology & Systems Biology (Meyer lab) Wednesday, March 25, 2026 Title of the Position
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enthusiastic group of interdisciplinary scientists interested in applying statistical genetics, and functional genomics and model cellular and organismal systems to study hematopoiesis in complex
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external) . Position Overview : We are looking for a highly motivated and qualified postgraduate trainee to join the project team. This individual should have experience in python programming including
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. Qualifications: An MS degree is required. A background in computer programming, whether through formal Computer Science training or applied experience is required. This individual should have
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predict molecular subtypes and therapeutic responses. These tools power a precision oncology framework that enables data-driven treatment selection. In parallel, we generate patient-derived 3D
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non-coding CRISPR screens, the Massively Parallel Reporter Assay (MPRA), saturation mutagenesis, and synthetic sequence design, alongside machine-learning models of regulatory grammar. Responsibilities
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-throughput experimental approaches such as non-coding CRISPR screens, the Massively Parallel Reporter Assay (MPRA), saturation mutagenesis, and synthetic sequence design, alongside machine-learning