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germ-free and conventional mice Perform high-dimensional data analysis (single-cell/spatial transcriptomics, genomics, metabolomics, immunoprofiling) and integrate findings with clinical datasets
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at Grape Genetics Research Unit (GGRU), USDA's purpose is to understand the grapevine response to environmental stressors like cold/freezing, drought, heat, and nutrient stresses. The research goal is to
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of infectious diseases. • Experience with data analysis using statistical inference techniques. • Experience with health economic evaluations. • Experience with parallel and/or high-performance computing
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), including during a postdoctoral fellowship. Experience with high-performance computing centers as well as with modern statistical software (R, etc.) and programming languages (Python, etc.). The candidate is
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their as-manufactured state using industry-standard non-destructive testing (e.g. ultrasonic testing). You will also develop microstructure-informed modelling to evaluate in-service performance throughout a
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calculations. Conduct Accurate Calculations: Perform accurate wavefunction calculations on high-performance computer clusters to generate ab initio reference benchmarks. Collaborate and Publish: Work closely
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from the Department of Civil and Environmental Engineering. This position is part of an exciting research programme aimed at advancing the multi-robotic wire-arc directed energy deposition technology and
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data storage and usage of high-performance computing resources provided at University of Michigan (Turbo Storage Globus, DataDen) Gene Expression Omnibus (GEO) data deposit for manuscript submission and
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. This role focuses on developing and applying AI and deep learning techniques for analyzing high-dimensional omics data, identifying predictive biomarkers, and understanding cancer heterogeneity. Projects
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laboratory team members to ensure high performance and skill development Foster cross-functional collaboration with research teams, industry partners, and international collaborators Coordinate work across