225 cloud-computing-"https:" "https:" "https:" "St" "St" Postdoctoral positions in Germany
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Field
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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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particle physics, computer science or a related field Experience with large-scale data management using grid or cloud technologies Experience in one of the on-site experiment would be an asset Familiarity
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English (at least B2 level according to the CEFR: https://go.fzj.de/languagerequirements ), ideally supported by a certificate confirming the language level. Knowledge of German is not prerequisite
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Max Planck Institute for Astrophysics, Garching | Garching an der Alz, Bayern | Germany | about 1 month ago
Job Code: 01/2026 Job Offer from January 29, 2026 Applications are invited for a postdoctoral research position focused on the development of advanced computational and statistical methods
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Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Is this you? Are
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Researcher in Computational Linguistics / Cognitive Science (m/f/d, E13 TV-L, 100%) The position will be filled for a fixed term of three years. Payment is at 100% of pay scale E13. The position is associated
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applications for the department AG Dichgans on the 1st April 2026, in full time, for Postdoctoral Researchers in Vascular Biology, Neuroscience, or Computational Biology – CRC 1744-funded (m/f/d) Scope of duties
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2026 - 23:59 (Europe/Berlin) Country Germany Type of Contract Temporary Job Status Full-time Hours Per Week 39 Is the job funded through the EU Research Framework Programme? Other EU programme Is the Job
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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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. 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