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EUMETSAT - European Organisation for the Exploitation of Meteorological Satellites | Darmstadt, Hessen | Germany | 9 days ago
; Lead the functional analysis, the definition, the prototyping and the scientific evaluation of algorithms used in the level-1 and level-2 processing chains for current and future EUMETSAT satellite
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for machine learning, with research topics ranging from decentralized and federated optimization, adaptive stochastic algorithms, and generalization in deep learning, to robustness, privacy, and security
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for machine learning, with research topics ranging from decentralized and federated optimization, adaptive stochastic algorithms, and generalization in deep learning, to robustness, privacy, and security
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responsible approach to implementing, verifying, and documenting algorithms Excellent proficiency in spoken and written English Willingness to work on-site at least 3 days per week at the Fraunhofer HHI
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techniques as well as in algorithms, statistics and artificial intelligence for molecular genetics; 3-year funding to work on your doctoral project. Up to two additional positions will be funded by a DAAD
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++, Python, and JavaScript languages, multi- and many-core SoC, RISC-V, hardware synthesis, hardware-software co-design, (meta-heuristic) optimization algorithms, machine learning frameworks, (bonus topics
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that process planning has a high potential for automated optimization. Building upon this, you will advance our optimization pipeline and evaluate different optimization algorithms/strategies. What you will do
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. About your role: Develop improved physical models of the image formation process in holographic X-ray imaging Design and implement reconstruction algorithms for handling large-scale tomographic data from
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: build a digital twin in Isaac Sim/Lab for the robot cell; mirror the real setup with matching kinematics, collision geometries and dynamics Algorithm Implementation: Develop and deploy reinforcement
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, aiming to explore and develop AI algorithms, frameworks, and hardware architectures for efficient edge deployment in vehicles, with a focus on neuromorphic computing. You will be part of the scientific TUM