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Deadline 5 Jan 2026 - 22:59 (UTC) Type of Contract Temporary Job Status Not Applicable Hours Per Week 40.0 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the
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modelling of pavement structures. The section’s state-of-the-art experimental and computational facilities support research from chemical and microstructural characterisation (FTIR, DVS, DSC) to full-scale
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their university education in: Mathematics, especially differential equations. Numerical methods and/or computer programming. Cloud physicsIt will be advantageous if the applicant is experienced with modeling
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application! Your work assignments The primary focus of this PhD position will consist in generating bioengineered models of human trigeminal pain, implement them in organ-on-a-chip systems emulating trigeminal
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explainable physics-informed RNNs for autonomous navigation and neural observer design within the broader framework of Embodied AI. The goal is to integrate physical models with deep learning to create
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Simulation Group at ICN2 conducts cutting-edge research in computational materials science, focusing on electronic structure methods, atomistic simulations, and multiscale modelling. The group develops and
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of Bradford. This PhD studentship is integrated into work package 5 of the ERC Synergy Subnordica Project, which will combine data from across the entire project into a set of predictive models for comparative
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learning models to forecast and visualize heat flow and occupant comfort metrics. Identify key drivers of energy inefficiency, including occupant behaviour patterns and physical heat loss hotspots. Formulate
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physical techniques eg laser and optical instrumentation; computational/numerical modelling programming skills eg Python, FORTRAN, C++. Eligibility Open to both UK and International applicants, including EU
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highly customisable multiphysics CFD framework for laser drilling and integrate it into accelerated industrial workflows. You will: Extend XCALibre.jl with new (traditional and/or AI-enhanced) models