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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description [Background of the recruitment and description of the project] * Background
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-inflammatory, or immunomodulatory), and work closely with computational collaborators to prioritize microbial strains and BGCs for experimental characterization. In addition, the fellow will maintain accurate
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Deadline 5 Feb 2026 - 12:00 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
background in microbial genomics, evolutionary biology, bioinformatics, or computational biology, with an interest in translational applications that connect bacterial evolution to clinical impact. Experience
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Recently it was discovered that enormous solar storms have occurred in
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level. The position requires working collaboratively with a team of experimental and computational biologists to integrate genetic and genomic data with mathematical modeling to better understand
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new research project funded by the Florida Institute of Oceanography’s (FIO) Florida Restore Act Centers of Excellence Program (FLRACEP). The project is being conducted in collaboration with researchers
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-December 2025 Group or Departmental Website: https://baronelab.org/ (link is external) https://biology.stanford.edu/ (link is external) https://hopkinsmarinestation.stanford.edu/ (link is external) How
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computational and machine learning approaches, you will decipher genomic regulatory programs and infer the evolutionary patterns of gene regulatory networks in cortical neurons, study their developmental origin
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: Using biogeochemical evolutionary models to simulate lifeless and inhabited worlds, and Developing disequilibrium-, redox-, and information-based metrics to understand and quantify the influence of life