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methods for image classification including machine learning and deep learning. You will develop clear workflows that allow for regular update of the derived models and maps. Furthermore, you will work
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100%, Zurich, fixed-term We have an open PhD position in Human-Computer Interaction with a focus on intelligent and adaptive systems for Augmented Reality, Mixed Reality, and Extended Reality
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understanding of travel behavior and mobility. Our research has strong conceptual and theoretical foundations, is ideally based on primary data, uses a mix of methods, and tries to infer causality as strongly as
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languages (in addition to Python) Experience with signal processing Familiarity with experimental design and empirical validation methods optional but useful: prior experience with AR/VR and Unity/Unreal
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future scenarios. Specifically, we will use spatially explicit surrogate models, which can accurately approximate the complex outputs of computationally expensive transport simulations in a fraction of the
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plasma. The main methods used are computer simulations for studying dust dynamics and analysing in situ measurements by spacecraft that carry a dust detector on board. We collaborate with researchers in
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efficiency, particularly with respect to latency. Project background The successful candidate will join the BMIC team at ETH Zurich and also be a part of the Computer Vision Lab (CVL). The project is conducted
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science journey, from the collection and management of data to machine learning, AI, and industrialization. The Center comprises a multi-disciplinary team of data and computer scientists and experts in
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. Empa is a research institution of the ETH Domain. The Urban Energy Systems Laboratory develops methods and tools to model, design and assess energy systems at various scales with a focus on energy hubs
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(SCI), lower back pain, neuro-degenerative disorders and neurological tumors. At the core of our research is the collaboration across disciplines spanning expertise in medicine, biology, computer and