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Are you a MSc graduate with background in data science, computer science, biostatistics, bioinformatics or a related field? Do you have a solid foundation in machine learning? Are you passionate
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Background in machine learning or deep learning methods, including Graph Neural Network (GNN) Experience with Large Language Models (LLMs) applied to biological data collection, extraction, and standardization
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of Virginia (UVA) School of Medicine is seeking to fill Postdoctoral Researcher positions in computational biology and machine learning. The lab develops modern machine learning, generative modeling, and
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than 18,500 people, including over 14,000 students and 4,000 researchers from more than 120 different countries. Postdoctoral Position in Computational Genomics, Machine Learning & Single-Cell Biology Mission
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single-cell and single-nucleus multi-omics, machine learning/AI, computational biology, and experimental validation to understand cardiovascular disease progression and identify novel therapeutic targets
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of response and develop predictive models. The work will involve analysis of large-scale datasets through multiomics integration, machine learning, statistical genetics, QTL analysis and development of genetic
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education and economic development needs. Federally designated as a senior military college, one of the university's signature leadership programs is its 800-member Corps of Cadets on UNG's Dahlonega Campus
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-doctoral research position under the supervision of Dr. Chris Smith Home | Chris Smith . Our lab studies spatial population genetics, using simulation-based inference and machine learning to infer
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well as introductory nutrition courses. The successful candidate will teach introductory biology courses and upper-level courses in their area of specialty. The successful candidate will also provide a proposal
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insights into actionable strategies for pediatric care. Our work combines statistical and mechanistic mathematical modeling, causal inference, and machine learning, applied to longitudinal multi-omics data