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enhance the competencies of the Institute in one or more of the following research areas: foundation models and efficient training/adaptation methods on HPC systems, generative AI and multimodal learning
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methodologies such as petrography, mineralogy and chemical (elemental and isotope ratio) analysis methods. We seek candidates who can capitalise on this investment and in addition can contribute to research in
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social dimensions of environmental interventions, including perceptions, behavioral aspects, and governance structures. A core component of the position is contributing to the design and operation of
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• Programming skills (e.g., Python, MATLAB, R) • Experience with AI/ML methods or power system modelling Conditional Offer The award of the PHAETHON PhD Studentship is strictly conditional upon the candidate’s
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the development of high-fidelity multiphysics models of existing research infrastructure, as well as novel system architectures and emerging energy concepts under investigation. A central component of the position
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in modelling, simulation, or data analysis of energy systems Knowledge of machine learning or artificial intelligence methods Programming experience (e.g., Python, MATLAB or similar tools) Experience
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instruments; Apply laboratory techniques to measure the organic carbon content of soils subject to different treatments; Use standardized rating scales and sampling methods to ensure accurate and consistent