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candidates will have: A solid grounding in mathematical or physical sciences Interest in dynamical systems and complex system behaviour Some coding experience (Python and/or Julia) Enthusiasm for working
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derive generally applicable guidelines for the design of improved organic materials. Interested candidates may want to take a look at our recent work https://www.nature.com/articles/s41467-025-67722-4 and
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applications. Experience in natural language processing, model evaluation, or experimental design is advantageous. Proficiency in Python and/or R and familiarity with AI/ML libraries or generative AI platforms
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project suits applicants with strong quantitative skills, an aptitude for coding, and an interest in textual analysis, large language models and computational methods. Previous experience in Python/Matlab
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by Renew Risk Ltd. (https://www.renew-risk.com/ ), offering opportunities to work with real offshore wind farm models and industrial datasets while addressing real-world challenges in collaboration
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Supervisor: Dr. Kamila Maria Jozwik, Jozwik lab PhD fees status: Home fees only (https://www.postgraduate.study.cam.ac.uk/finance/fees/what-my-fee-status ), 4 years Start date: October 2026 The
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official call documentation: https://marie-sklodowska-curie-actions.ec.europa.eu/actions/doctoral-networks Direct link to the project: https://cordis.europa.eu/project/id/101227124 Applications must be
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employment policies. For further information on the WIRe scheme visit the web site at: https://cdtwire.com/ The project based at The University of Sheffield will be supervised by academics at Sheffield and
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. Experience in coding (e.g., Python/R/Matlab) and experience in behavioural experimentation, statistics, or machine learning is desirable but full training will be provided. Interviews for this studentship
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conducting experiments, programming experimental tasks in platforms such as oTree, analysing experimental data using statistical and econometric software (e.g., Python, R, Stata), and reporting experimental