38 computational-physics "https:" "https:" "https:" Postdoctoral positions at Nature Careers
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-body physics nonequilibrium quantum dynamics, to quantum computation, quantum information, and machine learning. The Institute provides a stimulating environment due to an active in-house workshop
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field soil and will be conducted as part of the N2CROP project [https://mbg.au.dk/n2crop ]. Your profile We are looking for a highly motivated candidate with a keen interest in legume-rhizobium
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a master’s degree (if he/she applies for a position as research assistant) or a master’s and Ph.D. degree (if he/she applies for a position as a postdoc) in Bioinformatics, Computational Biology, or
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will involve both experimental and computational work and the candidate is expected to be comfortable with both. The candidate is expected to have (or be close to finishing) a Ph.D. in molecular biology
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). This project is funded by the DFG priority program SPP2474, which aims to discover new gene functions in human microbiome members (see https://spp2474.de). More information about ongoing research in
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Applications are invited for a position as postdoc in Computational Biology in the laboratory of DNRF Chair and Novo Nordisk Faculty Professor Vijay Tiwari (https://www.tiwarilab.org
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. The candidates must hold a PhD in Chemistry/Physics. Experience in data framework development, kinetic/thermodynamic modeling, and collaborative interdisciplinary research. An education history in chemical
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of the faculty. It offers successful candidates a fully-funded three-years position to prepare and submit their funding proposal for either an ERC grant or the Emmy Noether programme. In case funding is granted
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will begin on April 1, 2026. Job description Microbial life in anoxic environments often relies on tight physical interactions that enable cells to function, conserve energy, communicate and regulate
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(or near completion) in computer science, machine learning, statistics/biostatistics, computational biology, data science, physics, or a related field. Experience with modern deep learningframeworks (e.g