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) invites applications for a fully funded 4-year PhD program in Process Systems Engineering. The project aims at integrating data-driven optimisation and design of experiments techniques with model-based
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datasets, modelling approaches, and performance metrics; develop physics-informed and data-efficient machine learning models to predict sorbent behaviour from sparse and multi-modal experimental data; and
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models, molecular biology and sequencing. The student will be expected to attend and present in local and international meetings and conferences. The main objectives of the studentship will be: To carry
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-based surface hopping (X-SH). Applications will be carried out in collaboration with experimental groups aiming to understand at atomistic resolution how electronic excitations (``excitons”) dissociate