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contribute to advancing simulation-based testing methods for ADS. You will contribute to cutting-edge research projects, including the EPSRC-funded SimpliFaiS: Simplification of Failure Scenarios for Machine
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contribute to advancing simulation-based testing methods for ADS. You will contribute to cutting-edge research projects, including the EPSRC-funded SimpliFaiS: Simplification of Failure Scenarios for Machine
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and time-resolved spectroscopic studies on such systems using laser-based methods and characterizing reversible interactions between such complexes and biomolecules is desirable. You will be integrated
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to deliver the pre-registration BSc Speech and Language Therapy (SLT) Degree Apprenticeship programme. The BSc SLT Apprenticeship is delivered online and runs alongside our campus based BMedSci Speech and
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Using Brain Computer Interface to Improve Cognitive Performance School of Electrical and Electronic Engineering PhD Research Project Self Funded Dr Mahnaz Arvaneh Application Deadline: Applications
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-01126-2 Purshouse RC, Deb K, Mansor MM, Mostaghim S, Wang, R. A review of hybrid evolutionary multiple criteria decision making methods. Proceedings of the 2014 IEEE Congress on Evolutionary Computation
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Computational Spectroscopy/Hydrogen-tunneling at elevated temperatures in the gas-phase School of Mathematical and Physical Sciences PhD Research Project Self Funded Prof AJHM Meijer Application
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A search for pharmacological inhibitors of a cancer-associated adhesion GPCR in the zebrafish embryo
are seeking a motivated student with interests in developmental biology, disease modelling and drug discovery. This interdisciplinary project combines both wet bench work and computational work (bioinformatics
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Interplay between Algorithms and Combinatorics School of Computer Science PhD Research Project Directly Funded Students Worldwide Prof Parinya Chalermsook Application Deadline: 31 July 2025 Details
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experience of treatment. The overarching aim of the project is to use machine learning methods to understand why many people who are referred for treatment will drop out prematurely. To do this, two studies