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Field
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the program will receive training in genomic analysis, experimental modeling, translational science, and preclinical modeling of childhood hematological malignancies. The training program will equip the next
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or Environmental Engineering or a related field, including hydrologic and earth sciences, systems analysis, data and information science, or hydroclimatology. Demonstrated expertise in hydrologic modeling. Ability
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other sources to train and validate AI models. Develop computational workflows incorporating LLMs, Monte Carlo Tree Search (MCTS), phylogenetic inference, uncertainty quantification, and epidemiological
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mouse models. * Experience with cell and molecular biology techniques including PCR, western blotting, flow cytometry, cell culture and immunohistochemistry assays. Position Summary: The successful
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Postdoctoral Associate in Optimization Modeling The School of Civil and Environmental Engineering at Cornell University seeks a postdoctoral associate. The positions can be remote (but the home location needs
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. Description We are looking for a postdoctoral computational biologist to decipher the genomic regulatory code controlling gene expression in plants. Within the ERC-funded multiCODE project, we aim to unravel
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, and generalized additive models would be a bonus. Skilled in descriptive analysis and applying modern statistical methods in modeling of data. Technical writing and computer programming skills. Strong
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understanding of geomagnetic field evolution across different timescales, including both stable and extreme periods. This will involve working with data-based models and numerical dynamo simulations
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either or both agent-based modeling and social network analysis/network science. The ideal candidate should be able to program in C or C and have experience working with tera-bytes of data. Preference
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collaborative research program at the intersection of lipid biology, cell death, and evolutionary genomics. The project, primarily led by the Atilla Laboratory (Department of Chemistry ), investigates how lipid