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The Robotic Materials group at ETH Zurich Department of Materials is looking for three postdocs and one PhD for the project funded by ERC Starting Grant : "Distributed Addressable Robotic Material
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? No Offer Description The Robotic Materials group at ETH Zurich Department of Materials is looking for three postdocs and one PhD for the project funded by ERC Starting Grant : "Distributed Addressable
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Offer Starting Date 1 Nov 2025 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number BAP-2025-579 Is the Job related to staff position within a
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PhD positions in optically multiplexed soft robotic actuators The Robotic Materials group is looking for two postdocs and one PhD for the project funded by ERC Starting Grant : "Distributed Addressable
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Université de Technologie de Belfort-Montbéliard | Belfort, Franche Comte | France | about 1 month ago
), Dedicated HPC solvers (domain decomposition, parallel/distributed computing), Formulation and solution of optimisation problems (automation, optimal structural design). The developments will follow open
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group , led by Prof. Glenn van de Ven, is part of the Department of Astrophysics . The research group constructs detailed dynamical models of galaxies and stellar clusters to infer the distribution
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of Vienna . We are looking for a Senior Scientist to join the 'Dynamics of Stellar Systems' research group led by Prof. Glenn van de Ven. Our ideal candidate has a solid background in computational
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of Stellar Systems' research group led by Prof. Glenn van de Ven. Our ideal candidate has a solid background in computational astrophysics, strong track record in software development, and keen interest in
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for a Senior Scientist to join the 'Dynamics of Stellar Systems' research group led by Prof. Glenn van de Ven. Our ideal candidate has a solid background in computational astrophysics, strong track record
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Bayesian approach (Lages, 2024). Techniques used: Computational modelling, Bayesian inference, sampling and simulation techniques, prior distributions and posterior predictive checks, model comparison