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Using Brain Computer Interface to Improve Cognitive Performance School of Electrical and Electronic Engineering PhD Research Project Self Funded Dr Mahnaz Arvaneh Application Deadline: Applications
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the DFG Priority Programme “Molecular Machine Learning” and embedded in the research project “Multi-fidelity, active learning strategies for exciton transfer in cryptophyte antenna complexes”. The PhD
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full-time Programme duration 6 semesters Beginning Only for doctoral programmes: any time Application deadline Any time Tuition fees per semester in EUR None Combined Master's degree / PhD programme No
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phenomena at the interface between relativistic quantum field theory and condensed matter physics The essential part of the program is collaboration with Dr. Maksim Ulybyshev (Wurzburg University, Germany
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spoken and written is required The candidat must have a PhD in computer science, machine learning, or computational biology The position is available immediately and will remain open until filled
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communication skills and a passion for interdisciplinary research §you like tackling complex problems, working at the interface of biology, chemistry, and computer science, and publishing your results in top-tier
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Planck Institute of Colloids and Interfaces (MPI-KGF) Teaching language English Languages All activities are in English. English, German and French courses are offered. The PhD thesis may be written in
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Our objectives are the design, synthesis and thorough
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The Machine Learning for Integrative Genomics team at Institut Pasteur, headed by Laura Cantini, works at the interface of machine learning and biology, developing innovative machine learning
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the interface of plasma physics, quantum electrodynamics, and computational modeling. Your qualifications PhD degree in physics Knowledge of laser-plasma physics Theory and modelling of ultra-intense laser-matter