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administration and organisation. We are looking for a/an University assistant predoctoral/PhD Candidate Optical Quantum Computing and Machine Learning 51 Faculty of Physics Startdate: 01.02.2026 | Working hours
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and scalable. Design and build a technology demonstrator prototype of clinical-testing grade. Collaborate with interdisciplinary teams, including clinicians, engineers, and machine learning (ML) and
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regions. Machine learning provides a promising route to capture these relationships more systematically by identifying how local geometric features determine the resolution required for reliable prediction
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combines synthetic biology, machine learning, and biosensor and pathway dynamic regulation design to produce next-generation bio-based chemicals. The Computational Synthetic Biology group (CSBG), led by Dr
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these challenges by: Developing predictive workload, lead-time estimation, material planning models to capture the high variability in HMLV environments using hybrid AI (combining machine learning, feature-based
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2,900 work in administration and organisation. We are looking for a/an University assistant predoctoral/PhD Candidate Optical Quantum Computing and Machine Learning 51 Faculty of Physics Startdate
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candidate in the exciting area of multiscale and multiphysics modelling of sustainable fibrous composites, with additional focus on uncertainty quantification and machine learning. Information The context
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integrating modeling, machine learning (ML), and advanced control methodologies. The research will focus on designing AI-driven algorithms to assess battery health, predict degradation trends, and optimize
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rearing insects. Moreover, you will extract plant chemical compounds in the lab and learn how to analyze them. The research will be conducted in close collaboration with the University of Neuchâtel. You
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well as the programmes in statistics, cognitive science and innovative programming. Read more at https://liu.se/ida The position is based at the Division of Statistics and Machine Learning (STIMA). We conduct research