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Combining models and combining data / Realistic simulation of clinical trials Developing LLMs to utilise ODEs and ProbML as tools, Code synthesis for causality Generalisability, transportability and
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• Constrained experimental design • Combining models and combining data / Realistic simulation of clinical trials • Developing LLMs to utilise ODEs and ProbML as tools, Code
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modelling, and advanced regression techniques, ensuring transparency and reproducibility. Use and maintain high standards of coding practice for data processing and analysis, preferably using R, including
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to taking up the appointment. The research requires experience in electronic structure theory. Experience in R-matrix theory, quantum molecular dynamics, and the calculation of observables, as well as coding
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-dimensional data such as structural and/or functional neuroimaging or omics information, and/or temporal data as recorded using smartphones and/or wearable devices Excellent statistical and coding skills with
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genomic variation and phenotypic traits, predict gene essentiality, and model evolutionary trajectories. The role involves using large language models as coding assistants for efficient pipeline development
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MoSS with various diffraction methods, to develop code to automate the characterisation of MoSS with diffraction and other methods. The successful candidate will be involved in the supervision of a PhD
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MoSS with various diffraction methods, to develop code to automate the characteri sation of MoSS with diffraction and other methods. The successful candidate will be involved in the supervision of a PhD
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of galaxy formation, particularly from the COLIBRE project Develop software for the analysis of simulation data Contribute to further developments of the COLIBRE code This post is fixed term for 12 months
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-versa. Digital Humanities methods can broadly consist of familiarity with skills like coding, data scraping, archiving, data visualization, relational databases, or digital storytelling, but may not be