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on the design of AI-based surrogates of large-scale energy system models and will be integrated in the activities of the Nexus-e group with close links to the ETH AI Center and the Reliability and Risk
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reasoning and interaction capabilities including RAG, in-context learning, chain-of-thought reasoning, and agentic workflows with external tools. Trustworthy AI evaluation and confidential deployment: develop
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chemistry Ideally with expertise in bioelectronics or software simulations, or a strong willingness to acquire it, alongside solid knowledge of electrochemistry and materials chemistry Candidates should be
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line with our values , ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity
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equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and
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. Where to apply E-mail lorraine.dubuis@unige.ch Requirements Research FieldPsychological sciencesEducation LevelPhD or equivalent Skills/Qualifications Desired profile: PhD in psychology, neuroscience
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Hospital, Copenhagen). The successful candidate will be responsible for designing and implementing the predictive modeling strategy of the project. This includes: Developing machine-learning prediction
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charge of your own research You will take part in the professorship’s academic and social activities You will teach one course of your choice per semester (2 weekly hours) in the MAGPW or SiP programs
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-doctoral researcher to join our team. In the project, we will be analyzing ride-sharing, shared e-scooter and shared bicycle behaviour. We will analyse the data to understand the impacts of changes in supply
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optical simulation skills (Preferably in Zemax) Strong programming skills (preferably in Python) Experience in deep learning algorithms is a plus Ability to work in a highly international team and