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About the role We are seeking a full-time Postdoctoral Research Assistant to join the Computing Infrastructure research group at the Department of Engineering Science (central Oxford). The post is
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Postdoctoral Research Associate in Sum-Frequency Generation Microscopy of Biomolecular Self-Assembly
can apply for this position by submitting the following documents through the MPG postdoc program website (https://postdocprogram.mpg.de/node/21092 ): Motivation letter detailing your background, reason
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Research Council and led by the University of Exeter (you will report to Professor Kate Saunders in Oxford). The post is based in the Department of Psychiatry at the Warneford Hospital Oxford. The post is
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Research Council and led by the University of Exeter (you will report to Professor Kate Saunders in Oxford). The post is based in the Department of Psychiatry at the Warneford Hospital Oxford. The post is
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candidate will design and develop digital twin algorithms for computational fluid dynamics, contributing to innovative solutions in healthcare software systems. This role involves collaboration with research
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permeability selection in variant membrane chemistries. This work will run in parallel to experimental analysis conducted at the University of Exeter using synthetic vesicles to observe permeability
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in physics, mathematics or any related field; correspondingly, Postdocs hold a PhD or equivalent degree in the abovementioned fields. What we offer State of the art on-site high performance/GPU compute
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About us The Department of Informatics is looking to recruit a Postdoctoral Research Associate. We are a globally recognised center of excellence in artificial intelligence, robotics, and computer
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Applications are invited for a Postdoctoral Research Assistant in Ion Trap Quantum Computing. The post is available initially for a fixed-term duration of 3 years, with the possibility of extension
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environments, cloud computing, or GPU-accelerated machine learning Background in Monte Carlo Tree Search (MCTS) or reinforcement learning for sequence generation Familiarity with biological sequence alignment