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23 Dec 2025 Job Information Organisation/Company University of Siegen Research Field Computer science » Computer architecture Researcher Profile First Stage Researcher (R1) Positions PhD Positions
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related in space and time and to behavioral events. Core Tasks: Getting familiar with the experimental data and the concepts of neuronal coding, and Elephant Analysis of the parallel rate data for
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Karlsruher Institut für Technologie (KIT) | Karlsruhe, Baden W rttemberg | Germany | about 2 months ago
organisation. Where to apply E-mail jobportal@careerservice.kit.edu Website https://jobs.pse.kit.edu/en/jobs/169369/scientific-associate-fmd-in-computer-sc… Requirements Additional Information Website
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program generation and optimization Verification, testing and security of software systems Explainability of AI and of software engineering Software for distributed, highly-parallel AI systems Intelligent
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) The Institute of Computer Engineering (ZITI) at Heidelberg University invites applications for one research assistant position with the possibility to do a PhD in parallel at the chair of computer architecture
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processing and inversion techniques to experimental data from different regions and link the findings to relevant processes of the soil-plant system. For further information visit our website http://www.fz
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-edge Machine Learning applications on the Exascale computer JUPITER. Your work will include: Developing, implementing, and refining ML techniques suited for the largest scale Parallelizing model training
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engineered 3D hydrogels, we will experimentally probe the mechanical forces and physical constraints that drive coordinated cell behavior. In parallel, we will develop and apply computational models and
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on the Exascale computer JUPITER. Your work will include: Developing, implementing, and refining ML techniques suited for the largest scale Parallelizing model training and optimizing the execution User support in
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build reliable, reproducible data flows for large EO datasets and workflows Lead performance engineering (parallelization, optimization, benchmarking) for adaptation and inference at scale Work closely