351 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" positions in Switzerland
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the use of hierarchical graph neural networks for modeling multi-scale urban energy systems. By combining advances in Physics-Informed Machine Learning (PIML) and Graph Neural Networks (GNNs) with real
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foundations of conversational AI as well as domain knowledge on how and why it can be deployed effectively. You should have knowledge and skills in both data analytics (e.g., machine learning, statistics
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knowledge and technology from research to Swiss machine, electrical and metal industries. The research group Control and Automation at inspire AG offers the following position in collaboration with Bota
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Computer Vision and Computer Graphics techniques to digitize human avatars and garments in 3D. Within this project, your role is to advance our existing algorithms that reconstruct 3D garments from multi
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thinking with a structured, quality-focused approach to data and methods. Ideally, experience in one or more of the following: data engineering, building data-driven apps, computational linguistics, machine
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of machine learning, AI, and cancer genomics. Our lab develops novel machine learning methods to understand biological systems and cancer, with a strong focus on genomics and translational impact. We work in
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experience working in collaboration with biological or clinical labs and with groups with a strong machine learning background. The starting date is by mutual agreement. We expect a pronounced interest in
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the environmental drivers that regulate these processes. We will use machine learning approaches (XGBoost, SHAP analyses) for the flux partitioning, complemented by existing tree dendrometer and sap flow measurements
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of machine learning and high-performance computing, tackling complex, open-ended challenges to deliver scalable solutions. You will design and optimize a software-defined infrastructure that enables cutting
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library. Strong interest in machine learning, reinforcement learning, and fluid dynamics. Ability to work independently and collaboratively in an interdisciplinary team. Excellent command of English, both