57 assistant-professor-computer-science-data PhD positions at University of Birmingham
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predictive checking, model comparison) • Computational modelling with Python and Dynesty, JAX, NumPyro, and PyTorch • Use of asteroseismic and spectroscopic survey data (e.g. PLATO, Gaia, APOGEE, TESS) • High
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programme) clearly stating the title of the project and the name of the supervisor, Dr. Miguel Navarro-Cía (m.navarro-cia@bham.ac.uk ). Funding notes: Applications are sought from highly motivated students
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International Ocean Discovery Program (IODP) Expedition 395 (June-August 2023), has shown tipping point behaviour during the Pliocene in the deep-water return flow of the AMOC (Sinneseal et al. 2025). The aim
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validation in representative environments. The successful candidate will gain expertise in electrochemical sensing, microengineering, and computational modelling, and will join an interdisciplinary research
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candidate with a strong quantitative background (e.g., in computer science, statistics, bioinformatics). The following skills are essential for this project: Excellent programming skills in Python. Proven
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Main description: Native mass spectrometry is an expanding structural biology tool to elucidate the function of protein complexes. Excitingly, the demand for this technology is increasing. However
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This project is an exciting opportunity to undertake industrially linked research in partnership with the Manufacturing Technology Centre (MTC). It is an interdisciplinary PhD in Engineering from
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, which is currently supported by prestigious and large initiatives including QuSIT and a newly awarded Royal Academy of Engineering (RAEng) Research Chair on distributed radar systems. Finally, it will
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for the next generation of models is the detailed treatment of spin precession and orbital eccentricity. These effects encode critical information about compact binary formation channels and evolutionary
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-informed machine learning (PIML) with domain-specific engineering knowledge. By embedding physical laws and corrosion mechanisms into data-driven models, the research will produce more accurate