406 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "U.S" uni jobs in Sweden
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within data-driven Life Science research. More information about NBIS can be found at https://nbis.se . Duties We are looking for someone who wants to help enable life science research in Sweden that goes
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-driven Life Science research. More information about NBIS can be found at https://nbis.se. Duties We are seeking a candidate who wants to help enable life science research in Sweden that goes beyond what
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percent of working hours Contract terms The Doctoral student positions is fully funded from start. The position is a fixed-term appointment of four years, with the possibility to teach up to 20%, which
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at https://nbis.se. Duties We are seeking a candidate who wants to help enable life science research in Sweden that goes beyond what is achievable by individual researchers, a single university, or a single
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, and troubleshooting system failures Handover to incoming operators on shift changes Radiation safety tasks when necessary Machine development, automation, and documentation tasks The role of Accelerator
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cases, this can be slightly prolonged). The position will be placed at Timur Shegai's research group at Chalmers. You can find more information about the group at: www.shegai-lab.com or https
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-energy devices. Using state-of-the-art electronic-structure calculations and machine learning methods, you will model these effects and contribute to the design of improved semiconductors for solar cells
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terms The Doctoral student positions are fully funded from start. The position is a fixed-term appointment of four years, with the possibility to teach up to 20%, which extends the position up to five
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, workplace learning, educational leadership, communication, school development, didactics and teaching. For more information about doctoral education in education at the University of Gothenburg: https
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-order modeling, or machine learning Experience collaborating in interdisciplinary research teams What you will do Develop hybrid quantum–classical methods to improve simulation and prediction