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Field
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reproducible research software and scalable data analysis pipelines in Python for machine learning and interpretability research. These tools will support systematic investigation of model behaviour and enable
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a relevant field and have strong quantitative and analytical skills, including experience in food systems modelling or closely related areas. Proficiency in data analysis and coding (e.g. Python, R
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a PhD in Physical Sciences or a closely related field, and you will have a background in crystallisation and solid state characterisation. Knowledge of databases, and python coding is a must. The key
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language such as Python, MATLAB, R or NCL. Proven ability to work both independently and as part of a team. Experience of disseminating findings through scientific publications and conference presentations
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proficient in software development (e.g., using Java, Python, C++), with object-oriented programming and software engineering practices. You will have hands-on experience in designing, building, modifying
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in machine learning and/or advanced analytical methods, experience working with complex or large-scale datasets, and strong programming skills (e.g., Python or R). You will be able to communicate
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software (e.g. ArcGIS, QGIS) and coding environments (e.g. Python or R), collaborating across LUMHR themes, and supporting interdisciplinary research activity. Teaching support may be required, up to a
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nearing completion) in Bioinformatics, Computational Biology, Genomics, or a related field, and proven experience in analysing high-throughput sequencing data. They will be proficient in R and/or Python and
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and to solve major global challenges. About you You will hold a relevant PhD/DPhil in Cognitive Neuroscience, Psychology, or a related subject. Strong programming skills (Python and/or MATLAB) and the
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or a closely related field, and you will have a background in crystallisation and solid state characterisation. Knowledge of databases, and python coding is a must. The key responsibilities