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this centre, we are opening a PhD position on remote sensing of mountain forest dynamics. The Technical University of Munich (TUM) is one of the leading universities globally. At the TUM School of Life Sciences
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | 4 days ago
for deciphering organic matter dynamics in the Arctic Ocean (f/m/d) Background The Helmholtz School for Marine Data Science (MarDATA) is looking for a graduate in computer science, computer engineering, applied
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substrates while advancing our understanding of deep learning through dynamical systems theory. You will work with two cutting-edge experimental systems: (1) light-controlled active particle ensembles
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, Quantum Sensors Appl Deadline: 2025/09/31 11:59PM (posted 2024/09/24, listed until 2025/09/31) Position Description: Apply Position Description The position (post-doc, research associate, or PhD student
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Your Job: As part of your doctoral project, you will focus on hydrogen storage and release from liquid organic hydrogen carriers (LOHC) with alcohol functionality. Your focus will be on investigating the change in the catalysts surface under relevant process conditions using spectroscopic...
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Your Job: As part of your activities, you will carry out investigations of the continuous butanediol dehydrogenation under dynamic hydrogen release using pressure control in the laboratories
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methods like ZX-calculus) towards description of quantum noise employ such extended methods for quantum circuit compilation, optimization and error mitigation collaborate with theoretical computer
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bridging theoretical physics and theoretical computer science. In the course of this, you will work on implementing efficient simulators for continuous and discrete variable systems with noise based
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10.03.2023, Wissenschaftliches Personal We are looking for a motivated Ph.D. student or post-doc interested in developing novel processes that boost the production of bio-based liquid fuels and
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at demonstrating how teacher learning can be made robust in an event-based framework, that is, when both the teacher model and the learning rules are event- based. The combination of excitable teacher dynamics and