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modelling, or machine learning). Proficiency in statistical programming (e.g., R, Python, Stan, or similar). Experience developing and managing longitudinal studies. Evidence of contributions towards
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programming language such as Matlab, Julia or Python Experience in the development and analysis of mathematical and computational models of real-world phenomena Strong interpersonal, communication and
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econometric skills and proficiency in statistical programming using software such as Stata, R, or Python. Experience with administrative data and knowledge of advanced techniques, including structural
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-level proficiency in R (and/or Python) for data wrangling, modelling, visualisation, and reproducible reporting workflows demonstrated capability in managing and analysing large, complex datasets with
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skills using R, Stata, SPSS, MPlus or Python. Experience managing nationally representative survey datasets and conducting complex statistical analyses (including multilevel modelling and SEM). Here's how
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. Ability to undertake complex analyses and data modelling using programming languages such as Python, R and/or hydrological modelling packages, with adherence to FAIR data principles (Findable, Accessible
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; sound programming skills, with a strong preference for MATLAB; experience in other scientific programming languages (e.g. Python, R) is also valued; familiarity with international macroeconomic and trade
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dynamics or fisheries. Proven experience and ability programming in R or Python. Proven experience and interest in the application of mathematical modelling techniques to model the ecology of wildlife
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-temperature conditions. Proficiency with data analysis tools and scientific programming languages (e.g., Python, MATLAB, LabVIEW). Commitment to safe laboratory practices and familiarity with experimental risk management
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/ML/CV venues Proficiency in Python and deep learning frameworks Experience in machine learning, computer vision, or NLP Strong communication and collaboration skills Our commitment to inclusion and