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languages such as Python, R or MATLAB. Role Summary Implement and test different ML architectures for postprocessing precipitation forecasts over India. Determine how to maximise information extracted from
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with a strong data-driven or machine learning focus. Essential Skills & Experience Strong programming skills (Python essential) and experience with scientific computing libraries. Experience building
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analysis of behavioural experiments Strong quantitative and programming skills, and knowledge of one or more relevant programming languages (e.g. Matlab; Python; R). Experience with, or an understanding
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of scientific programming, e.g. with C++, Python, ROOT or similar. Informal enquiries to Professor Dave Charlton, email: dave.charlton@cern.ch View our staff values and behaviours here Use of AI in applications
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computing (e.g. Python, MATLAB, or similar) for data processing and data handling Experience with data processing, analysis and interpretation Excellent interdisciplinary communication – Strong collaborative
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to scientific problems, preferably with materials or polymer datasets. Proficiency in Python and scientific computing libraries; familiarity with machine-learning frameworks and data processing tools. Experience
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strong track record in programming, preferably in Python. The candidate should have demonstrable expertise in computational modelling of solids, preferably using density functional theory methods. Previous
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instrumentation, and computing (C++, Python) Informal enquiries to Cristina Lazzeroni, email: c.lazzeroni@bham.ac.uk Use of AI in applications: We want to understand your genuine interest in the role and for