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Biology with both high-throughput experimental (proteomics and genomics) and integrative computational (network analysis and machine learning) methodologies, aiming to understand gene functions and their
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to: Manuscripts, reports, abstracts for conferences, grant proposals Data analysis and pipeline development Technology-based solutions for advancing population health To be eligible, candidates must: Have received
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such as Cornell’s Transportation Environment Analysis Model for Cities (Cornell TEAM-Cities), the emerging urban transportation, environment, and community health modeling Hub (uTECH Hub), and the
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multidisciplinary team, contributing to design, data collection, policy analysis, prototyping, and dissemination. Candidates with expertise in any area—policy, AR/VR tools, community engagement, or programming
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the appointment start date; demonstrate strong expertise in computational biology or data-driven modeling, with experience in one or more of the following areas: machine learning or deep learning, structural
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for conferences, grant proposals Data analysis and pipeline development Technology-based solutions for advancing population health To be eligible, candidates must: Have received a PhD in computer
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at scientific conferences. • Contribute to the CNCPS development and support outreach efforts to disseminate findings to nutritionists and producers. Anticipated Division of Time Research 50% Data analysis 40
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Systems Engineering (Health Systems Data Analysis, Modeling, Computing, and Cloud-Based Health Systems Analytics and Decision Support Platforms) as part of the CTECH Postdoctoral Fellows program. This
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and pangenome scale analysis of fungal pathogens of agricultural crops. Anticipated Division of Time Lab and Computational Research: 40% Field and Greenhouse Research: 20% Writing, Data Analysis, and
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producers. Anticipated Division of Time Research 50% Data analysis 40% Writing 10% Requirements Ph.D. in Animal Science, Dairy Nutrition, Feed Science, or a related field. Strong background in ruminant