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, Division of Computational Biology) on research using large-scale EHR data sources, including Epic Cosmos and PEDSnet. Ideal candidates will have experience in one or more of the following areas: EHR-based
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Fritz Haber Institute of the Max Planck Society, Berlin | Berlin, Berlin | Germany | about 3 hours ago
Job Offer from April 21, 2026 The Fritz Haber Institute in Berlin is one of the most internationally renowned research institutes of the Max Planck Society for the Advancement of Science. More
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. The selected candidate will join an interdisciplinary team, working closely with scientists in the Physics Department and BNL Computing and Data Science (CDS) to develop the application of cutting-edge
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. The duties and responsibilities for this position will be to: 1) Analyze data with the STAR/LHCb experiments. 2) Contribute to the EIC physics program and the optimization of the EPIC backward HCAL project
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will receive full consideration. Key Responsibilities AI-ready data and analysis for the ePIC Barrel Imaging Calorimeter and our Jefferson Lab program Support for the PRad-II and X17 experiments
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techniques: handling biological samples, extracting nucleic acids from blood and tumors, PCR, Sanger sequencing, mass sequencing (NGS panels), DNA methylation analysis (EPIC array), and results analysis (0
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make a difference in the world! Position Information Postdoctoral Research Associate in Agricultural, Animal, Rangeland, or Environmental Sciences Location: Texas A&M AgriLife Research, Temple, Texas
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/bioinformatics, and data science. Work Performed · Work in highly collaborative inter-disciplinary environment with clinicians, econometricians, statisticians, and data scientists · Lead statistical analysis
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with process-based models, including APEX, SWAT, EPIC, DayCent, or DNDC. Proficiency in computer programming, including scripting in Python, Fortran, or other computing tools for data processing and
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Argonne National Laboratory invites applications for a postdoctoral research position in experimental physics, with a focus on advancing superconducting particle detector technology for next