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Education (CLUE), a new project being developed jointly between ETH Zurich EPFL, is an interdisciplinary initiative dedicated to advancing research and practice in learning and education across the lifespan
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science journey, from the collection and management of data to machine learning, AI, and industrialization. The Center comprises a multi-disciplinary team of data and computer scientists and experts in
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and Computer Science AI/Machine Learning Nanotechnology/Devices (more...) Artificial Intelligence, Machine Learning and Autonomy Health Tech Microelectronics BioNanotechnology Material Science and
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100%, Zurich, fixed-term We are seeking a skilled Machine Learning Engineer to join our dynamic team. The ideal candidate will be involved in the development, optimization, and maintenance of our
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experimental reactor physics benchmarking analyses. In 2020 the PETALE experiment was conducted at the CROCUS reactor at EPFL in Switzerland. This position will create a benchmark evaluation for the
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cantonal and federal administrations. The center accompanies and supports their entire data science journey, from the collection and management of data to machine learning, AI, and industrialization. As part
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. students. The institute has also published at most of the major machine learning, computer vision, and robotics conferences, including CVPR, NeurIPS, ICCV, ECCV, ICML, ICLR, IROS, AISTATS, as well as in
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are required to have: A completed PhD degree. Experience in machine-learning methods. Some skill in at least one of these topics: Large data sets analysis Statistics and uncertainty analysis (probabilistic
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Apply machine learning techniques for data analysis and time-series forecasting Collaborate in a multidisciplinary team to accelerate functional thin film development Your work will be part of a larger
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• Skilled in single-cell/population data analysis (e.g., GLMs, decoding) Preferred Qualifications • Background in machine learning or computational modeling (Bayesian methods, neural networks, etc