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Infrastructure? No Offer Description Work group: JSC - Jülich Supercomputing Centre Area of research: PHD Thesis Job description: Your Job: We are looking for a PhD student to contribute to the development of fast
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branch offices) is available at https://www.fz-juelich.de/en/careers/phd The contract will be with Forschungszentrum Jülich, but the daily place of work will be at University of Cologne in the group
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Infrastructure? No Offer Description Work group: IAS-6 - Theoretical Neuroscience Area of research: PHD Thesis Job description: Your Job: This PhD project bridges between classical analytical methods and modern AI
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Infrastructure? No Offer Description Work group: IAS-6 - Theoretical Neuroscience Area of research: PHD Thesis Job description: Your Job: This PhD project aims at relating precisely timed spike constellations
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Infrastructure? No Offer Description Work group: JSC - Jülich Supercomputing Centre Area of research: PHD Thesis Job description: Your Job: We are looking for a PhD student to develop learning-based surrogate
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information on doctoral degrees at Forschungszentrum Jülich (including its various branch offices) is available at https://www.fz-juelich.de/en/careers/phd We welcome applications from people with diverse
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information on doctoral degrees at Forschungszentrum Jülich (including its various branch offices) is available at https://www.fz-juelich.de/en/careers/phd We welcome applications from people with diverse
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at Forschungszentrum Jülich (including its various branch offices) is available at https://www.fz-juelich.de/en/careers/phd We welcome applications from people with diverse backgrounds, e.g. in terms of age, gender
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at Forschungszentrum Jülich (including its various branch offices) is available at https://www.fz-juelich.de/en/careers/phd In addition to exciting tasks and the collaborative working atmosphere at Forschungszentrum
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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