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), regulatory science, pharmacometrics, and real-world evidence (RWE). The successful candidate will develop AI-driven systems to support regulatory document intelligence, automated pharmacokinetic modeling, and
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dynamics for shape change. A further aspect of the project is learning and calibrating these models from data using data-driven inference methods. Who we are looking for Required qualifications A doctoral
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., Pettersson, H., Behrens, A., Männik A., 2018. Comparing a 41-year model hindcast with decades of wave measurements from the Baltic Sea. Ocean Engineering, 152, 57–71. https://doi.org/10.1016/j.oceaneng
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considered for this PhD, please follow the instructions here: https://www.centre-ub.org/studentships/application-process/ Fully funded 4-year PhD studentshipat the University of Birmingham. Scholarship covers
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simulations. Data-driven materials discovery: ML models for property prediction, materials design, or synthesis optimization. AI/ML methods development: Neural networks, graph neural networks (GNNs), generative
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UPOs PhD enrolment: Université Paris Cité DC15: Hybrid machine learning models for data-driven bioprocess optimisation PhD enrolment: University of Padua Eligibility Requirements: Doctoral Candidates