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for more information. About you To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria 1. PhD degree in Engineering, Computer
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developmental science. The successful candidate will contribute to a major research programme investigating how educational experiences shape mental health from childhood into adulthood. The role involves working
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About us We are looking for motivated researchers to apply for the postdoctoral research associate position in robotics and AI, funded by our new EPSRC project titled “Circular Robot 5.0: Industry Wide Data-Driven Circular Economy of Industrial Robots”. The candidates are expected to have...
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machine learning tools and working on Linux High-Performance Computing platforms would be highly desirable. This is a highly collaborative role and you will work with scientists and clinicians from other
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development laboratories at Guy’s Campus, London Bridge. The group specialises in inventing custom fluorescence-lifetime and multiphoton technologies and coupling them with powerful computational pipelines
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at the Barts Cancer Institute (Queen Mary University of London). This role will involve analysing existing spatial-omics data sets and developing novel computational tools to understand the risk of developing
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"Mathematical Data Science" research group at the University of Vienna (led by Prof. Dr. Philipp Grohs) and the "Computational Partial Differential Equations" research group at TU Wien (led by Prof. Dr. Michael
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spectroscopy Experience Proven experience in algorithm development to do physiological signal processing Experience in advanced computational techniques to assess and enhance signal quality Experience in machine
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students and over 500 Single Honours undergraduate students. We offer a 3-year BSc degree programme in Biological Sciences and a 4-year MBiol, while also contributing to Natural Sciences. We also run a PGT
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at the Barts Cancer Institute (Queen Mary University of London). This role will involve analysing existing spatial-omics data sets and developing novel computational tools to understand the risk of developing