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, in a relevant topic and relevant experience with mathematical modelling of infectious diseases. Strong knowledge of a programming language (e.g. R, Python) is essential. Experience in mathematical
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. Candidates must also have excellent programming skills in a relevant scientific language, such as Mathematica or Python, to facilitate advanced data analysis of measurement outputs. Apart from being able
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Professor Carl Thompson, you will lead and deliver our SENSITISE research project, helping develop it into a longer programme of work and helping disseminate our research findings in imaginative and impactful
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of epidemiological modelling and data analysis C2 Up-to-date knowledge of epidemiological modelling approaches C3 Knowledge of relevant programming languages for model development, for example Java, R, C++, Julia C4
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modelling. Experience in cybersecurity, including vulnerability assessment, threat detection, and incident response. Proficiency in programming languages such as Python, Java, or C++, and experience with AI
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of strong programming skills in R, Python, or other open-source programming language. Further particulars are included in the job description. The post is full-time, 1.0 FTE and fixed-term for 3 years
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learning, anomaly detection, and predictive modelling. Experience in cybersecurity, including vulnerability assessment, threat detection, and incident response. Proficiency in programming languages such as
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and commercial tools (e.g. XCMS, MZmine, Compound Discoverer, GNPS, SIRIUS, etc). Proficiency in one or more programming languages (e.g. R, Python). Experience with continuous integration and best
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date: 19th June 2025 Background To create and contribute to the creation of knowledge by undertaking a specified range of activities within an established research programme and/or specific research
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reinforcement learning, and explainable AI (xAI)) Strong knowledge of sustainable energy systems, particularly V2G technology and grid-edge flexibility, proficiency in programming in Python, with experience in ML