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currently exploring a range of exciting topics at the intersection between computational neuroscience and probabilistic machine learning, in particular, to derive mechanistic insights from neural data. We
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networks, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our
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control engineering, optimization algorithms Control of drones and flight experiments as well as knowledge in AI / Machine Learning would be an asset Outstanding academic records Teamworking experience, e.g
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platforms involving sensors, instrumentation, and physical measurements Involvement in the design, wiring, commissioning, and troubleshooting of systems Collaborate closely with PhD students, postdocs, and
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preferably adopt a systems-level approach and make use of high-throughput methodologies. Effective application of advanced machine learning analysis and data integration approaches, potentially through