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join us as a PhD candidate. You will work in a highly interdisciplinary group, at the intersection of physics, machine learning and theoretical neuroscience. Our group is focused on investigating
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recent advances in machine learning and browser automation, the project aims to provide tools, techniques and datasets to effectively address these threats. As a PhD candidate, you will play a key role in
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-analysis, regression modelling, machine learning). You have a solid basis in at least one common high-level programming language (e.g. R, Python). You enjoy collaborative research in international
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? You hold a PhD degree in ecology or environmental science. You have proven experience with quantitative analytical methods (meta-analysis, regression modelling, machine learning). You have a solid basis
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PhD candidate, you will contribute to both aspects, from studying the brain’s control of movement to applying these insights in the development of closed-loop brain–computer interfaces aimed
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Job related to staff position within a Research Infrastructure? No Offer Description Join a transformative project at RIBES using machine learning and genomics to overcome linkage drag and accelerate
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) training opportunities. Would you like to learn more about what it’s like to pursue a PhD at Radboud University? Visit the page about working as a PhD candidate . Where to apply Website https
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and help supervise BSc and/or MSc students during their internships with us (10% of your working time). Would you like to learn more about what it’s like to pursue a PhD at Radboud University? Visit
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electron ground states. Another promising route towards physical implementations of energy-based machine learning and neuromorphic hardware is to utilise material platforms that exhibit multiwell behaviour
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you eager to make AI more sustainable? As a PhD Candidate, you will develop innovative methods for predicting and reducing the energy consumption of large-scale AI systems during their design phase