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and develop software which enhances the learning experience. Grow your professional skills using C#, JavaScript, continuous integration and automated deployment and get experience and training with
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of a relevant PhD qualification. The title of Lecturer will be applied upon successful completion of the PhD. The candidate should have a background in quantitative methods or applied/social statistics
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excellent knowledge of advanced statistical methods and experience in analysing large-scale datasets, as well as solid practical experience in the use of STATA, R or a similar software package, and good
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to gender—and demonstrated expertise in advanced statistical methods (e.g., multilevel modelling). The successful candidate will work closely with the Principal Investigator, Dr. Verena Klein, a PhD student
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conditions. Our work combines traditional statistical methods with advanced artificial intelligence algorithms to identify patterns in disease. We also use qualitative methods to understand lived experiences
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cognition and emotion processing. We invite applications from individuals with a background in human experimental psychology (participant recruitment, experimental testing, data analysis) and with a PhD in
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different sources Share data, software and models including experimental and simulation data Deploy close-to-data computation and containerisation of data and software Use AI to explore data Make the results
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complex health and social care challenges, particularly in the management of long-term conditions. We combine AI and traditional epidemiology with qualitative methods to develop impactful, real-world
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students. All cohorts have now been recruited and are in the delivery phase of their PhDs until 2027. PhD projects are AI-focussed with a mix of hardware and software, focussing on the areas of Agent-based
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research in ship hydrodynamics, design optimisation, and marine decarbonisation. Our work combines advanced simulation, AI, and experimental methods to support a more sustainable maritime future. The Role