225 computational-physics "https:" "https:" "https:" "https:" "U.S" Postdoctoral research jobs in Germany
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matter properties Physics » Statistical physics Physics » Computational physics Researcher Profile Recognised Researcher (R2) Positions Postdoc Positions Country Germany Application Deadline 6 Feb 2026
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) Application Deadline 30 Jan 2026 - 12:37 (UTC) Country Germany Type of Contract To be defined Job Status Other Offer Starting Date 5 Jan 2026 Is the job funded through the EU Research Framework Programme? Not
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adaptive systems that jointly optimize morphology and control for real-world physical interaction. Requirements Ph.D. in Computer Science or a related discipline. Strong background in Machine Learning
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Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | 3 months ago
physics, applied mathematics, or a related field, as well as an interest in biological and soft matter physics. Expertise in studying pattern formation, elasticity theory, statistical physics, or biological
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neutrino astronomy.At its Zeuthens location, DESY has a strong focus on astroparticle physics (https://www.astro.desy.de ). In particular, we host one of the largest groups in IceCube and play a leading role
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plant development. PLoS computational biology, 15(6):e1007121, 2019. doi: 10. 1371/journal.pcbi.1007121. URL https://journals.plos.org/ploscompbiol/article?id=10.1371/ journal.pcbi.1007121 . D. E. Moulton
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25 Feb 2026 Job Information Organisation/Company Constructor University Bremen gGmbH Department School of Science Research Field Computer science Researcher Profile Recognised Researcher (R2
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Informatics Initiative (MII)/FHIR standards Design and implement methodological concepts and software for benchmarking frameworks for AI evaluation Independently develop and implement research ideas within
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Max Planck Institute for Astrophysics, Garching | Garching an der Alz, Bayern | Germany | about 1 month ago
of Gaussian Process regression methods defined on graph-based domains Integration of these methods into the NIFTy framework Contribution to the design and maintenance of the MW-Atlas compute infrastructure
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. In the ELUD research project, we address the question of if and when learning agents converge to an efficient equilibrium and when this is not the case. ELUD will design new algorithms for computing