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identification of deterioration processes and assessment of their evolution/extent. Please reach out to the primary supervisor, Prof. Craig Hancock , if you have any questions. Entry requirements: We are looking
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samples. All computational methods and algorithms will be implemented as part of the python based MetaboLabPy platform (https://doi.org/10.3390/metabo15010048 , https://github.com/ludwigc/metabolabpy
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computational research, part-funded by the European Regional Development Fund through Welsh Government. The brand-new building of the Computational Foundry provides an ideal environment for doing a PhD. Funding
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provide powerful tools to improve the quality and efficiency of data-driven models. In parallel to the development of data-driven models for dynamical systems with geometric structures such as Hamiltonian
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: Machine Learning Molecular Dynamics. The project involves the development and application of machine learning methods that enable a major boost of the time and length scales accessible to ab-initio/first
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are conserved across reproductive development between the fern Ceratopteris richardii and the flowering plant Arabidopsis thaliana. https://www.biorxiv.org/content/10.1101/2025.03.18.643782v1
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for the academic year 2025/26) University fees and bench fees: The studentship covers bench fees, stipend, and tuition fees. Visa and associated costs are not funded. International applicants can visit https
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data-driven approaches, multi-scale model development and software development depending on the interest of the successful applicant. Big picture: The Tarzia Research Group (https
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modifications affect topoisomerase activity during C. elegans nervous system development. This multidisciplinary project provides advanced training in molecular genetics, genomics, and translational biotechnology
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to continuously learn, adapt, and refine world models in self-adaptive and autonomous systems. Specifically, the research will investigate how AI-based methods can support the evolution and updating of transition