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understanding and practical experience with machine learning approaches for biomarker discovery and predictive modeling, specifically with hands-on experience in developing and applying neuronal networks
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with the lab’s objectives. Support the next generation of scientists (PhD students, postdocs), fostering a collaborative and productive research environment. Key areas of support include design analysis
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of this project will bring forward the integration of novel methods at the intersection of advanced control, optimization, manufacturing science, robotics, and machine learning. The doctoral student position we
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that integrate machine learning with energy system optimization to make such policy optimization possible. The analysis will include policies for EV adoption, EV charging infrastructure, and electricity pricing
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the admission requirements for a PhD at ETH Zurich Experience in machine learning, optimization, or AI-driven decision-making Preferably with knowledge of Bayesian optimization or Gaussian processes
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We are seeking a highly motivated and interdisciplinary Postdoctoral Researcher to join our team in developing a cutting-edge nutrient prediction platform. This project integrates machine learning
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master’s degree preferably in Computer Science, Information Technology, Information Systems, Statistics, Data Science, Engineering, or a related field Strong machine learning and programming experience with
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experience with computer modelling, (e.g. agent-based modelling), as well as good grasp of machine learning, forecasting techniques, scenario planning, optimisation, Python and GIS. Good knowledge of English
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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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founded by Innosuisse and the project is in close collaboration with an industrial partner. Profile Applicants for the position are expected to have earned a PhD in heterogeneous catalysis with documented