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for a PhD position that combines research in the field of intelligent mission planning and learning-based optimization with real-world applications, in collaboration with Volvo Group. This is an ideal
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and machine learning to tackle the complexity of force allocation and motion planning under uncertainty and actuator failures. The project combines theoretical research in stochastic optimal control
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and/or practical experience with measurement techniques in fluid dynamics and heat transfer. Contract terms The position is limited to four years, with the possibility to teach up to 20%, which extends
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the Swedish National Infrastructure for Computing (SNIC) and the Chalmers Centre for Computational Science and Engineering (C3SE). Learn more about the project and the research: Project overview Due
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15 full-time researchers offers a stimulating and supportive environment to learn and grow. Your profile Required qualifications: Undergraduate degree in Engineering, Physics or Mathematics with strong
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team of over 15 full-time researchers offers a stimulating and supportive environment to learn and grow. Your profile Required qualifications: Undergraduate degree in Civil Engineering or a related topic
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courses, including several master’s programmes. Learn more at: www.chalmers.se/en/departments/e2 Qualifications To qualify, you must: Hold a Master’s degree (or equivalent, 240 ECTS) in Engineering Physics
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reinforcement learning, robotics, and the development of reactive software systems. It enables the creation of robust, reliable programs by specifying what a system should do, while automatically deriving how it
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accepted. The following experience will strengthen your application: Familiarity with Federated Learning We value a collaborative attitude and an interest in working both in teams and independently. Self
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passion for learning and a desire to work in a multidisciplinary and open team. Contract terms and what we offer The PhD-positions are fully funded from start As a PhD student at Chalmers, you are