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young team (Computational Systems Medicine) within the context of the BMFTR-funded DIASyM (https
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strongly supported by our college-level instructional design team for course development and delivery and by our research core for grant development and submission. Dr. Jinling Liu’s laboratory ( https
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strongly supported by our college-level instructional design team for course development and delivery and by our research core for grant development and submission. Dr. Jinling Liu’s laboratory ( https
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; neurobiology; signal transduction; cancer biology. We encourage candidates to build on existing strengths within the department (see our website at https://renaissance.stonybrookmedicine.edu/pnb
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, and lipidomics to investigate how these neural signals reshape systemic metabolism and aging. More broadly, the Lyu Laboratory investigates how the brain interprets environmental information and
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by neural circuits and translated into systemic physiological responses. We combine Drosophila neurogenetics, optogenetics, connectomics analysis, metabolomics, and lipidomics to investigate how these
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development of ProteomicsDB with a good background in bioinformatics, data visualization, big data analytics at best in the context of mass spectrometry. ProteomicsDB (https://www.proteomicsdb.org/) is an
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sequencing, lipidomics and proteomics. Host institution: Vrije Universiteit Amsterdam, Netherlands Supervisor: Professor Martine Smit Keywords: Chemokine receptors • GPCRs • Nanobodies • Lipidomics Project 9
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<span lang="en">German Center for Neurodegenerative Diseases (DZNE)</span> | Bonn, Nordrhein-Westfalen | Germany | about 21 hours ago
, a deeply-phenotyped, large-scale population-based cohort study. Available data include comprehensive multi-omics data, including (epi)genomics, transcriptomics, metabolomics, lipidomics, and
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University of North Carolina at Chapel Hill | North Wilkesboro, North Carolina | United States | 12 days ago
biology and cloning * Bioinformatics or computational analysis experience * Experience working with large imaging or omics datasets (proteomics, metabolomics, lipidomics, spatial transcriptomics