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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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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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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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Alps documentation of the technical and scientific aspects regarding the geological model(s) in peer-reviewed papers and technical reports Profile MSc or PhD in Earth Sciences or closely related field
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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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-cultural. EPFL covers a wide spectrum of science and engineering and offers a fertile sSchool of Basic Sciences include theoretical and experimental biophysics, biological imaging and physics of machine
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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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industrial partner, you will design and implement innovative architectures for real-time detection and control of laser processes. This interdisciplinary role combines artificial intelligence and machine
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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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Early Development) and Genentech). Leverage state-of-the-art platforms, technologies, and Roche’s core facilities to advance your research. Mentor and guide graduate students through our joint PhD