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Doctoral Student - Enhancing Building Efficiency through Edge-based Machine Learning and Control We are looking for a doctoral student to join our international team and contribute to our research efforts
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Researcher or experienced Data Scientist to harness AI, machine learning, and statistical modeling on cutting-edge datasets in precision feeding, animal behavior and welfare, multi-omics and environmental
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experimental and simulated data, leveraging AI and machine learning techniques Contribute to novel computational optimisation methods for machining processes Develop and implement automation solutions, including
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of computationally efficient data-driven control and machine learning methods that enable deployment on edge devices with limited computation. We are looking for a motivated doctoral student to contribute
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is to leverage advanced machine learning to develop an automated design process of mechanical walking aids, analyse gait patterns, and make biomechanical simulations embedded in the generative
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contribute to diverse machine learning projects across ETH's research and administrative domains, developing and implementing scientific computing solutions to support various projects. Throughout all your
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to machine learning, AI, and industrialization. With a large multidisciplinary team of professionals across three locations (Lausanne, Zurich, Villigen), the SDSC provides expertise and services to various
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position in the area of Machine Learning for Engineering Design under the guidance of Prof. Mark Fuge, the Chair of Artificial Intelligence in Engineering Design. The general area of the laboratory covers
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, or HCI methods familiarity with adaptive systems or machine learning prior experience conducting user studies Beneficial background in computational interaction or adaptive systes knowledge of optimization
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classical approaches and machine learning. We look forward to strengthening our team with a colleague who contributes to our research and teaching, and is interested in gaining more experience and expanding