227 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"NOVA.id" positions in Switzerland
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upcoming areas off the beaten paths. Our three main areas of research are machine learning, distributed systems, and theory of networks. Within these three areas, we are currently working on several projects
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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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stable water isotope data, and Statistical analyses, including machine learning approaches. The full-time position is funded for four years. Salary and social benefits are provided according to ETH Zurich
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we seek to enhance resources for student learning on statistics and machine learning applied to these topics. Project background We would like to develop learning exercises that help students learn how
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only supports your professional development, but also actively contributes to positive change in society You can expect numerous benefits , such as public transport season tickets and car sharing, a wide
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Master’s students of national and international institutions Strong motivation to explore topics in human–computer interaction, learning technologies, and AI-assisted tools Experience or strong interest in
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modeling of historical controls, as well as machine learning, data science, and epidemiological studies based on large SCI datasets. This is an excellent opportunity to contribute to translational research
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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
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Computational Design Lab and work at the interface of computer vision, computer graphics, hardware, and extended reality. The project is part of ETHAR, a new research initiative at ETH Zürich with a unique focus
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to support a circular bioeconomy. We are seeking a highly motivated postdoctoral researcher to develop and apply machine‑learning and data‑science methods, with a focus on computer vision, to enhance wood