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to apply your expertise to real-world clinical challenges. To be successful, you will have: Postgraduate qualifications in computer science, data science, or a related discipline (PhD preferred
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evaluate methods via experiments, benchmarking, simulation and/or real‑world data. The successful candidate will have: A PhD in Statistics, Data Science, Computer Science, Mathematics, or a related field
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Proficiency in analytics, AI, and modern data science tools Excellent problem-solving, project coordination and communication skills A PhD or equivalent research experience (preferred) Experience with clinical
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data (e.g. DFT, MP2) and experimental data into AI-driven pipelines for structure–property learning and reactivity prediction. Applying AI models to real-world problems in virtual screening, ligand
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fast-readout electron detectors to validate the methods developed. The successful candidate will have a PhD in Physics, Materials Engineering, Computer Science or a closely related field. Research
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the University’s research capacity in a globally relevant field. The role provides the opportunity to develop and publish a monograph based on Korean Studies-related PhD research or, if already published
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multidisciplinary in nature, cutting across statistics, econometrics, operations research and data science. Specific project outcomes relate to multiobjective optimisation, expected shortfall and conformal inference
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peer-reviewed publications, while providing senior-level expertise to support and mentor internal teams. A vital responsibility includes guiding emerging science-practitioners (Clinical Psychology PhD