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in AI and machine learning – from classical approaches to large language models. You are proficient in Python and key ML libraries (e.g. scikit-learn, PyTorch, LLM APIs), and you have a track record of
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or Python. Working with the workstream Co-leads and wider research team, they will contribute to analyses, publications, reports and dissemination, as well as undertake administrative tasks and present
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(e.g. APMS) with software such as Stata, R, MPLUS, or Python. The successful candidate will contribute to publications, reports and dissemination activities, present findings at seminars, meetings and
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Python with demonstrable familiarity with PyTorch, experience in working on shared codebases, excellent applied math skills (especially probability theory, matrix algebra, calculus). Beyond technical
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to process data and/or answer quantitative research questions (e.g., but not limited to applications written in either R, Python, Julia, Go, Java, or C/C++). E3: Experience of scientific writing. E4: Proven