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project entitled "Energy Storage as an Enabler of Sustainability through Optimization, Machine Learning, and High-Performance Computing," supported by the Dieter Schwarz Foundation through a Courageous
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part of a project entitled "Energy Storage as an Enabler of Sustainability through Optimization, Machine Learning, and High-Performance Computing," supported by the Dieter Schwarz Foundation through a
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candidates hold a Master’s degree in Informatics, Mathematics, or a related field, and possess strong expertise in linear algebra, GPU architectures, and programming in C++ and Python. This is a 100% TVL E13
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23 Sep 2026 Job Information Organisation/Company Constructor Knowledge Labs gGmbH Research Field Computer science Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application
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architectures. Emphasis will be placed on heterogeneous computing and the optimal use of CPU and GPU resources to maximize model performance, scalability, and portability. A particular focus of the position will
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of computational systems biology and mathematics/statistics with a strong attitude to open research software development. For more information visit http://www.fz-juelich.de/ibg/ibg-1/modsim or http://github.com
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, microfluidics, laboratory automation, and GPU computing infrastructure. The opportunity to develop AI methods and scientific software that are directly deployed on cutting-edge experimental platforms. Vacation
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with a strong background in mathematics, computer science, or machine learning. The work has a strong focus on developing new objectives or new architectures for medical deep learning and on new ways
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Max-Planck-Institut für Struktur und Dynamik der Materie | Hamburg, Hamburg | Germany | 3 months ago
computing technologies and accelerator (GPU) computing. Familiarity with scientific software toolchains, including compilers, numerical libraries, parallel programming frameworks, and scientific software
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of machine learning and clinical oncology, with access to a large multimodal research dataset, substantial GPU resources, and a collaborative scientific environment. Your tasks Design and implement LLM-based