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explore, and how different ways of structuring learning environments influence curiosity and learning. Computational models will be used to characterise individual differences in information-seeking
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. In addition, the following are requirements for the role: Strong programming and quantitative skills, particularly in Python and/or R. Experience in deep learning, machine learning, or large-scale
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. Fluent oral and written communication skills in English. Desirable qualifications Documented Experience with Python and/or another scientific programming language. Documented Experience with image
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of different natures (gradient-based optimization, sampling-based methods, and learned policies) within a single coordination scheme. This involves assigning each subproblem to the most suitable approach and
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, for example using Python or comparable tools, and experience with GIS-based spatial analysis. The ability to work with heterogeneous geological, hydrogeological and monitoring datasets and to connect
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MRI data processing and analysis. Knowledge of cardiovascular physiology. Experience programming in MATLAB and Python. Experience in systems biology, mathematical modelling, and digital twins
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scientific applications. The CGR lab conducts research at the cutting edge of computational biology and bioinformatics. We aim to understand human genome variation and evolution across different genomic
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and programming languages e.g. Linux, Python, R. Excellent interpersonal and communication skills and ability to work with colleagues at all levels. Desirable Criteria Experience in multi-omics
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, and Den Otter, Weindel, Stuit, Van Maanen, Plos Computational Biology, 2026 for more information about these methods. The goal of the project is to be able to track differences in strategy use between
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, particularly in light of the rise in chronic diseases, the necessary strengthening of prevention efforts, or the possible resurgence of epidemics; socio-economic inequalities and differing capacities to access