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econometric and machine learning frameworks to analyse the causal relationships between transport behaviour, residential energy consumption, and environmental outcomes in urban systems. The successful candidate
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-intensive physics with nuclear/particle aspects, advanced detector R&D, machine learning and AI and emerging computational methods in quantum computing. The position is intended for an excellent and broadly
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cognition. Under the guidance of Prof. Jutzeler, a dedicated postdoctoral researcher, and collaborators, you will have access to unique clinical datasets, wearable sensing technology, and state-of-the-art
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collaboration with Philips Medical Systems. You will be part of a diverse and passionate research team of academic staff, PhD candidates and Postdoctoral researchers in the Computer Engineering group. Curious
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, towards future colliders. Cutting-edge machine learning developments for classical and quantum computational platforms are pursued in the group to benefit particle physics and beyond. Experience Candidates
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relevant if there is a strong focus on data-driven modeling, machine learning, and control. In any case, a documented background or experience in control is required. Your education must correspond to a five