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Field
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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 design nitrogen-efficient maize
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) of Florida Atlantic University (FAU) is seeking outstanding applicants to pursue postdoctoral training on the molecular mechanisms activated by drugs of abuse. The current focus of the lab involves the study
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highly motivated post-doc to finalize a research project on the molecular mechanisms of gene control in bacteria. The person to be recruited will study the transcriptional control of gene expression in
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encouraged. BSL-2 pathogens will be utilized. The successful applicant will be able to synthesize experimental data into conceptual models. The Kaelber lab is located in the Institute for Quantitative
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Postdoctoral Positions for Computational Genomics, Cancer Genetics, and Translational Cancer Biology
qualifications: Ph.D. in cancer biology, molecular biology, immunology, genetics, or a related field. Experience with cell and molecular biology techniques, animal models, immunology assays, or translational
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structure, atomic orbits, and model applicability domains Train and benchmark large-scale MLFF models on diverse molecular and materials datasets Integrate uncertainty estimates into active learning pipelines
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, Molecular Biology or related areas. Background in Mucosal Immunology, microbiota, allergy. Excellent communication skills in English. Proven ability to work independently within a research lab. Demonstrated
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synthesis. The Research Institute CEISAM is the molecular chemistry laboratory of Nantes Université, located in a recently constructed building that provides cutting edge facilities. CEISAM is located in
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? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The postdoctoral researcher will join the Molecular Imaging and Radiobiology team
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computational modeling. The postdoctoral candidate will: Analyze quantitative molecular and imaging data produced by other members of GENESIS. Develop new machine learning models to identify gene regulatory