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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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the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Post-doctoral Position in Machine Learning
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applications, including solving mathematical reasoning problems and tackling the Abstraction and Reasoning Corpus (ARC) challenge among others. The ideal candidate has a strong background in machine learning and
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Your profile PhD applicants must possess a Master's degree in mathematics, theoretical physics, or computer science. Candidates should have an exceptional academic record and a robust mathematical foundation. Candidates are also expected to have strong coding and implementation skills, with the...
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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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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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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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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