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aims to advance the field of time and frequency (TF) transmission in data communication networks. The focus of the research will be on distributed fiber optic sensing (FDOS) and machine learning
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to investigate flow-induced forces in hydraulic turbines under varying operational conditions and how these forces affect the degradation and lifetime of the machines. About the position The position is based
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will use machine learning methods to develop affinity ligands. These methods have been transformative for protein design, allowing generation of novel proteins which can suit a precise need. In this 4
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and documented background in machine learning, deep learning, data analysis and programming. Previous experience in research and knowledge in bioinformatics, biophysics, biochemistry, molecular biology
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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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application! Your work assignments Our research projects focus on distributed sensing, hardware-efficient signal processing, robustness and resilience, and communication-efficient decentralized machine learning
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the Division for Computer network and systems and the employment is placed with Chalmers University of Technology. Our research spans from theoretical computer science to applied systems development. We provide
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sustainable design, product development and environmental assessment will conduct case studies to integrate user behaviour into the early design of dishwashers, washing machines, refrigerators and ovens
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consist of the following: Mathematical analysis of ecological and eco-evolutionary models, involving pencil-and-paper calculations; Computer simulations of more complex models which do not easily lend
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totaling 60 ECTS credits) and join an international research team with backgrounds in sociology, political science, network science, statistics, and machine learning. More information on the PhD program can