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disease, including AI-powered tools and new statistical techniques that leverage large datasets, heavy computational capabilities, and/or a robust understanding of biological systems to provide unique
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experience working with large, complex data from varied sources. The candidate should have proficiency with statistical software, ideally Stata, strong written and interpersonal communication skills, and a
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-performance computing systems (,e.g., SLURM) Familiarity with population genomics, GWAS, or related approaches Experience with large biological datasets Proven ability to communicate scientific information
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one or more of the following areas is a BIG PLUS: data science (machine learning and AI), cancer biology, animal physiology, organic chemistry, E3-ubiquitin biology, and gene editing. In all cases
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engineering. We seek candidates with an interest in participating in large multi-PI grants and with collaborative research experiences, experience writing proposals for user-facilities, and/or experience
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the Rosaceae, Citrus, Vaccinium and Pulse crop databases to meet community demand for resources with usable big data aggregated, analyzed, integrated, and visualized, as well as data management and analysis
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for longitudinal data analysis or large language models. Strong motivation in the development and application of digital twins, particularly in health and biomedical contexts. Strong computer programming skills
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the tensor network simulations using HPC resources for selected case studies. Analyze simulated data and compare directly with RIXS experimental spectra; assist in data interpretation and (if applicable
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Description The Buckler/Romay Lab at Cornell University is seeking a Postdoctoral Associate to advance research on maize and grass molecular diversity using genomic large language models (AI). The goal is to
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running simulations or AI workflows on supercomputers Experience with training or applying large language models for research Experience with MPI and Input/Output (I/O), and data management Experience in