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24.09.2025, Wissenschaftliches Personal The Chair for Efficient Algorithms, led by Prof. Stephen Kobourov, invites applications for a fully funded PhD position at the Technical University of Munich
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algorithms for application parallelization, simulators and virtual platforms for application- and architecture exploration, hardware/software co-design and operating/runtime systems. Typical application
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computing to develop a continuous and local alternative to existing gradient-based learning rules, bridging theories of predictive coding with event-based control/ Simulate models of the learning algorithm
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quantum device calibrations, benchmarking, and run quantum algorithms Presenting and publishing the research on an international stage To apply, please submit a complete CV, letter of motivation, university
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diverse working day is guaranteed! During the project, you will develop and implement self-learning control algorithms that balance computational demand and modeling precision. You will evaluate, interpret
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diverse working day is guaranteed! During the project, you will develop and implement self-learning control algorithms that balance computational demand and modeling precision. You will evaluate, interpret
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of software interfaces and data models Selection and configuration of algorithms for annotating and organizing research data and software using state-of-the-art AI technologies Ensuring the sustainability and
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group focuses on developing strategies and algorithms to quantity biologic effects of particle radiation based on underlying physics, biology and physiology. Within the BMFTR funded project “BIOMICRO
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | about 2 months ago
on particulate and dissolved organic matter from hyperspectral absorption data sampled at Arctic expeditions at AWI’s Hausgarten (Fram Strait) in the last 10 years by optimizing established algorithms from
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format for the unambiguous and machine-readable characterization of software interfaces and data models Selection and configuration of algorithms for annotating and organizing research data and software