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Job Description Are you passionate about neuromorphic computing and hardware design? Do you want to contribute to the next generation of brain-inspired computing systems for healthcare applications
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that merge thermo-fluid dynamic laws, deep learning, and experimental data. A central goal is to overcome current limitations in TES operation and optimization, enabling discovery of new high-performance and
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automation Earth processing Computational fluid dynamics Numerical process modelling Rheology Furthermore, the candidate should be motivated to work collaboratively as part of a team. You must have a two-year
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experimental research in nanoparticle catalysis using advanced operando electron microscopy This collaborative PhD project between Technical University of Munich (TUM) ( the group of Prof. Barbara A.J. Lechner
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for intelligent brain-computer interfaces? We are offering a PhD position in analog/mixed-signal CMOS circuit design for EEG and wearable sensor interfaces, as part of a pioneering project focused on assistive
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general planning of the PhD study programme, please see DTU's rules for the PhD education . We offer DTU is a leading technical university globally recognized for the excellence of its research, education
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of the PhD study programme, please see DTU's rules for the PhD education . Assessment The assessment of the applicants will be made by Dr. Lei Yang and Prof. Johannes Kabisch (Norwegian University of Science
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characterization of glycoside hydrolases, and a postdoc working on computational modelling of the same enzymes. The PhD focuses on ligand-observed NMR analyses and other relevant methods to provide insight
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Offer Starting Date 1 Apr 2026 Is the job funded through the EU Research Framework Programme? Horizon Europe - MSCA Is the Job related to staff position within a Research Infrastructure? No Offer
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PhD scholarship in Runtime Multimodal Multiplayer Virtual Learning Environment (VLE) - DTU Construct
leading universities, research institutes, and industrial partners across Europe to deliver a world-class doctoral training programme in risk assessment, resilience engineering, and smart technologies. Its