23 machine-learning "https:" "https:" "https:" "https:" "https:" scholarships in Switzerland
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systems, and space applications. We combine theory, physics-based simulations, machine learning, and autonomous workflows to understand and design materials that can perform under conditions where
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combining advances in Physics-Informed Machine Learning (PIML) and Graph Neural Networks (GNNs) with real-world energy applications, the project aims to better capture the dynamics of urban infrastructures
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transfer, developing and employing computer simulations, laboratory experiments, and field analyses. Our aim is to gain fundamental insights and develop sustainable technologies to address societal needs
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essential, while experience with machine learning is advantageous but not strictly required. Excellent English skills, both in verbal and written communication, are required for the project. We are looking
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senior members in the lab, and at the same time to play an active role in shaping and creating inspiring research and working environment. In line with our and Uni Basel values (https://www.unibas.ch/en
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at the interface of machine learning, statistics, and live-cell biology. The position is co-supervised by Prof. Olivier Pertz (Cell Biology) and Prof. David Ginsbourger (Statistics), and the student will be equally
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rearing insects. Moreover, you will extract plant chemical compounds in the lab and learn how to analyze them. The research will be conducted in close collaboration with the University of Neuchâtel. You
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as well as profound knowledge of professional computer-aided design and 3D modelling In addition, you have experience in CAD/CAM (preferably McNeel Rhinoceros) and/or robotic fabrication, as
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are looking for highly motivated, committed, creative and eager to learn individuals, able to work in a team and with excellent communication skills. Working in a top-level research environment with advanced
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of applying molecular models at process scales, the project combines efficient mathematical concepts like automatic differentiation with backpropagation – the same concept that powers machine learning and