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multimodal machine learning approaches that remain robust while engaging with practical concerns of privacy, ethics, and user agency. Throughout this project, you will contribute to data collection experiments
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computing, hardware accelerators, performance engineering, energy-efficient computing, or machine learning. Your duties The position includes research, education and management. Key responsibilities include
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are looking for applicants who have or expect to receive a PhD degree before joining the project. Applications should have a relevant track record in multimodal machine learning, preferably in the context
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behaviour: (multiple) market places, collectives and networks. Simulations: computer experiments, digital twins, hardware in the loop experiments, computational economics/social sciences, network flows, agent
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. Empirical/experimental design and emergent behaviour: (multiple) market places, collectives and networks. Simulations: computer experiments, digital twins, hardware in the loop experiments, computational
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technologies, for example, using machine learning techniques to support long term exploration; Topics related to ‘off world living’, e.g. human factors, design and concept illustration; Crew Health and
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to develop your professional experience and competencies, to learn from ESA experts and to contribute to ESA activities. Technical competencies Experience with artificial intelligence and machine learning
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of either a hands-on laboratory based project and/or a software simulation and modelling project. Both projects will contribute to the preparation of future space science missions. The laboratory-based
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Do you want to play a crucial role in developing new applications for the next generation of computer technology? At CogniGron, a globally recognized research center of the University of Groningen
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architectures Ethernet, PCIe, JESD204, SpaceFibre, SpaceWire, CAN and MIL-STD-1553 interfaces System level modelling with Matlab, SystemC and/or SystemVerilog High-level synthesis and auto-coding Hardware