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)) models are used at all stages of pre-clinical and clinical development, but they are based on mathematical and statistical principles dating from the 1970s. Developing these pharmacometric models remains a
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is research experience in biomedical modelling and machine learning, statistical programming, an ability to produce high-quality academic writing, good communication skills, and an enthusiasm
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affect these trajectories using discontinuous growth modelling and/or other appropriate statistical analyses. Additionally, the student will conduct a qualitative interview study to understand
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is research experience in biomedical modelling and machine learning, statistical programming, an ability to produce high-quality academic writing, good communication skills, and an enthusiasm
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wide range of topics, including matching, scheduling, internet markets, and developing new algorithms and analysis techniques. Typical tools and topics are Probability and Statistics, Game Theory
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that students undertake in their studies. This will include use of software for experiment generation and statistical analysis. Liaise with other members of the Professional Services team in set up and
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required to create and develop a range of reports and will also support the preparation and submission of the institute’s reports to external agencies, such as the Higher Education Statistics Agency (HESA
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aptitude for research design and statistics and will have a background in psychology or a related discipline. They will be supervised by Dr Sam Farley, Dr Nicola Thomas, and Professor Jeremy Dawson from
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success in the German and/or EU market context. The successful applicant must have strong quantitative, statistical, and analytical skills. Demonstrated knowledge of Python and Machine Learning techniques
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mathematical skills in probability and statistics. Good knowledge of current state-of-the-art in safe AI and frontier AI systems, as well as experience supporting junior researchers and managing projects is