205 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:" uni jobs in Switzerland
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Your profile We seek candidates with an outstanding research record in deep learning, in particular in one or several of the following areas: modeling and architecture development, domain adaptation
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Scientist / Scientific assistant – Tree species detection using deep-learning Are you an ambitious data scientist with strong analytical and numerical skills, and expertise in geomatics, remote sensing, and
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Center for Project-Based Learning. The successful candidate will contribute to research at the intersection of embedded machine learning, signal processing, and smart sensing systems, with applications in
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80%-100%, Zurich, fixed-term We are looking for a Research Engineer to join ongoing and future research projects at the intersection of machine learning, and structural design (e.g. trusses, space
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Systems.”Funded through an ETH Zurich Career Seed Award, this project aims to develop scientific machine learning frameworks that integrate physics-based modeling with neural network architectures. The goal
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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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. • Familiarity with machine learning, dimensionality reduction, clustering, and statistical modeling. • Strong communication skills, interest in interdisciplinary work, and ability to train students and postdocs.
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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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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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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