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knowledge. We expect candidates to have previous experience in areas such as control engineering, reinforcement learning, field robotics. Furthermore, candidates should have excellent study results, very good
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Sciences division. This multidisciplinary team utilises a combination of machine learning and mechanistic modelling to derive models and scientific insights from data, which both support and enhance drug
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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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to doctoral studies, the applicant must have basic eligibility and have completed a degree in engineering/master's degree in computer engineering/computer science or equivalent, completed course requirements of
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to doctoral studies, the applicant must have basic eligibility and have completed a degree in engineering/master's degree in computer engineering/computer science or equivalent, completed course requirements of
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of MSI advances our understanding of complex brain processes. The prospective PhD candidate collects brain MSI data and develops novel machine learning methods in connection to generative models such as
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for Quantum Technology (WACQT, http://wacqt.se ). The core project of the centre is to build a quantum computer based on superconducting circuits. You will be part of the Quantum Computing group in the Quantum
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on the hypothesis that the future of building design lies at the intersection of physically sound building simulation models and machine learning (ML) techniques. Key considerations include effectively integrating ML
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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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, computer engineering, human-computer interaction, or equivalent by 2025-07. Demonstrate proficiency in English (reading, writing, speaking). Show the ability to work independently as well as in a team. Good