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We have 19 physics-informed PhD Projects, Programmes & Scholarships
physics-informed PhD Projects, Programmes & Scholarships
We have 19 physics-informed PhD Projects, Programmes & Scholarships
Advanced Wall Modelling for Magnetohydrodynamics Simulations Using Physics-Informed Machine Learning (Ref: AAE-HX-2501)
Magnetohydrodynamics (MHD) is critical in engineering applications such as fusion power plant design and metallurgical processes. Read more
A PhD Studentship in Optimal Control Strategies in Large-Scale Spatio-Temporal Maritime Systems Using Data-Driven Physics-Informed Machine Learning
Applications are invited for a PhD studentship, to be undertaken at Imperial College London (Control and Power Research Group, Department of Electrical and Electronic Engineering). Read more
Digital twins of engineering structural systems for optimal performance and sustainability
Are you ready to embark on a transformative journey in the field of computational mechanics, digital twins and artificial intelligence for engineering structures?… Read more
University of Bath LURS Studentship: Physics-informed machine learning models (PIML) for soft manipulators
The Department of Mechanical Engineering at the University of Bath is inviting applications for the following fully-funded PhD project. Read more
Last chance to apply
PhD in Water Resources: Next-Generation Flood Models: Physics-informed neural networks for urban resilience
Award Summary. Newcastle University, School of Engineering Funded Studentship. UKRI annual living allowance of £24,000, research grant + UKRI fees paid. Read more
Physics-informed modelling of osteocytes network formation
Unlike common belief, our bones are alive, filled with cells, and constantly remodelling. Osteocytes are the most abundant cells of our skeleton that live buried in the mechanically hard bone matrix and are the master regulators of bone remodelling. Read more
Artificial Intelligence for Environmental Fluid Dynamics Modelling
Supervisory Team. Gustavo de Almeida and Dr Sergio Maldonado. This PhD project explores the use of Physics-Informed Neural Networks (PINNs) to solve environmental flow problems, including the 2D Shallow Water Equations. Read more
Advancing Machine Learning for Extreme Wind Speed Prediction, Engineering – PhD
The University of Exeter’s is inviting applications for a fully funded PhD studentship to commence on on September 2025 (or sooner if appropriate). For eligible students the studentship will cover Home or International tuition fees plus an annual tax-free stipend of at least £19,237 for 3.5 years full-time, or pro rata for part-time study. Read more
Hybrid Modelling for Sustainable Formulation Design and Innovation
The Department of Chemical Engineering at the University of Manchester is offering a fully funded PhD position, co-sponsored by Unilever, offers a unique opportunity to work at the interface of academic research and industrial innovation, shaping the future of Fast-Moving Consumer Goods (FMCG) formulations. Read more
PhD in Machine Learning: Unlocking the Future of Cardiovascular Medical Diagnostics
PhD in Machine Learning. Unlocking the Future of Medical Diagnostics. Join our Dynamic Team in Sydney, Australia. Introduction. Read more
Decision support to deliver gravel barrier adaptation pathways mapped to system state triggers
This PhD is being advertised as part of the Centre for Doctoral Training for Resilient Flood Futures (FLOOD-CDT). Further details about FLOOD-CDT can be seen here https://flood-cdt.ac.uk/. Read more
Cost-Effective Protection Toolbox for DC Grids
These projects are open to students worldwide, but have no funding attached. Therefore, the successful applicant will be expected to fund tuition fees at the relevant level (home or international) and any applicable additional research costs. Read more
Incorporating Contextual Information and Physical Principles for Enhancing Short- and Long-Term Mobility Forecasts
I am recruiting students for a research project to advance short- and long-term mobility forecasting by combining neural network models with Newtonian physics principles and contextual (i.e., geographically distilled) information. Read more
Artificial intelligence as surrogate for finite element models of radiofrequency ablation treatment
The advent of computational technology has led to the development of various computational models and platforms that can predict the outcome of radiofrequency ablation (RFA). Read more
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