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world models with deep learning methods. World models are generative models that predict future outcomes given past ones. We aim to work with both images and audio modalities and be able to use the world
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(SWEET CoSi) and aims to build up new projects in the domains of circular economy and land use change. In addition to research, the successful candidate will contribute to teaching environmental economics
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Your position TwoPhD studentships are available to characterize health-relevant properties of aerosol particles. Our group develops novel instruments to measure continuously oxidising properties of aerosol particles in the ambient atmosphere and in laboratory experiments (e.g., Utinger et al.,...
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databases is a strong plus. Workplace Workplace We offer ETH (Swiss Federal Institute of Technology) and Eawag (Swiss Federal Institute of Aquatic Science and Technology) are world leading institutions in
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of Aquatic Science and Technology) are world leading institutions in Environmental Sciences. ETH and Eawag share a strong mandate in research, education and expert consulting and actively promote gender
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such as biology, medicine, chemistry, earth and environmental sciences, cultural heritage, materials and surface science, and physics. The ID19 beamline at the ESRF is a multi-purpose long (145 m) imaging
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and laboratory tasks constituting up to 10% of the work time. Profile MSc in Earth Science, in some cases a MSc in Environmental or Atmospheric Science would be considered if there is appropriate
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information science, focusing on spin qubits and hybrid superconducting-semiconductor quantum devices. This position is offered in a shared initiative between the laboratories of Prof. Wallraff and Prof. Scarlino
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100%, Zurich, fixed-term The laboratory of Single-Molecule and Single-Cell Biophysics (BMC)is a research group in the Department of Information Technology and Electrical Engineering (D-ITET) at ETH
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100%, Zurich, fixed-term The Energy and Process Systems Engineering (EPSE) Group at ETH Zürich is looking for a doctoral student to develop predictive methods for identifying sustainable chemicals