PhD Studentship: From Brittle to Ductile: Machine Learning 3D Fracture Simulations for Extreme Environments

University of Warwick
Coventry, University Of Warwick, Midlands Of England, United Kingdom
3 weeks ago
£21,805 pa
Applications closed

Related Jobs

View all jobs
Spotlight

Senior ML Compiler Engineer

Fractile Bristol, United Kingdom
Spotlight

Forward Deployed Engineer

SolveAI London, United Kingdom
Hybrid

Research Associate* in Machine Learning Aided Data Compression and Communication

Imperial College London London, United Kingdom
£49 – £57 pa On-site

Senior Deep Learning Engineer

NVIDIA United Kingdom
£221,250 – £507,000 pa Hybrid

Senior Deep Learning Engineer

£221,250 – £507,000 pa Hybrid

Senior Deep Learning Engineer

Senior Deep Learning Engineer

Senior Deep Learning Engineer

£221,250 – £507,000 pa Hybrid

Salary

£21,805 pa

Job Type
Contract
Work Pattern
Full-time
Work Location
On-site
Seniority
Entry
Education
Phd
Posted
9 May 2026 (3 weeks ago)

About the project:

From Brittle to Ductile: Machine Learning 3D Fracture Simulations for Extreme Environments

Supervisor: Prof, James Kermode, University of Warwick

Develop cutting-edge machine learning models to predict how materials break at the atomic scale. You'll create AI-driven simulations that reveal why tungsten, the leading fusion reactor material, transitions from ductile to brittle behaviour as the temperature drops, combining quantum mechanics, large-scale molecular dynamics, and deep learning.

Work with world-leading researchers at Warwick and the Max Planck Institute for Sustainable Materials, mastering scientific machine learning, uncertainty quantification, and high-performance computing.

Your models will inform fusion design and advance AI-for-materials. Perfect for physics, maths, or materials students wanting to blend fundamentals with real-world impact. Code, physics, and helping to solve the energy challenge, all in one project.

About HetSys: Harnessing Data, Modelling and Simulation for Real‑World Impact

HetSys (Centre for Doctoral Training inModelling of Heterogeneous Systems) at the University of Warwick is an innovative, interdisciplinary fully funded PhD programme that brings together science, engineering, and mathematics to tackle some of the most pressing challenges of our time.

  • Big Questions, Real Impact – From climate modelling and sustainable energy to advanced materials and biomedical systems, HetSys projects apply cutting‑edge computational and mathematical techniques to problems with global significance.
  • Interdisciplinary Training – Students gain expertise across physics, engineering, computer science, and applied mathematics, developing versatile skills that open doors to both academia and industry.
  • Collaborative Environment – Work alongside leading researchers and industry partners in a supportive, vibrant community that values curiosity, creativity, and collaboration.
  • Future‑Focused Careers – HetSys graduates are equipped with highly sought‑after skills in modelling, simulation, and data science, preparing them for impactful careers in research, technology, and beyond.

If you’re excited by the idea of using advanced modelling and simulation to solve complex, real‑world problems, HetSys offers the perfect environment to push boundaries and make a difference.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Where to Advertise AI Jobs in the UK (2026 Guide)

Where to advertise AI jobs UK in 2026: the specialist boards and communities that reach AI engineers, ML scientists and applied research talent in the UK. The candidate pool is small, highly informed and in demand across multiple sectors simultaneously. General job boards reach a broad audience but lack the specificity that AI professionals expect — and the filtering mechanisms they rely on. Specialist platforms, direct outreach and academic channels each serve a different part of the market. This guide, published by ArtificialIntelligenceJobs.co.uk, covers where to advertise AI roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about time-to-hire across different role types.