PhD Scholarship: The Self-Driving Microscope – Predicting Stochastic Failure in Solid-State Batteries Using Physics-Informed AI
University of Greenwich
London, United Kingdom
The University of Greenwich is offering a fully funded PhD scholarship focused on the development of a “self-driving microscope” to predict stochastic failure in solid-state batteries using physics-informed artificial intelligence. This interdisciplinary project sits at the intersection of materials science, artificial intelligence, and advanced imaging, aiming to address critical challenges in next-generation energy storage technologies.
The research will involve developing autonomous experimental systems that integrate microscopy with AI-driven decision-making to observe and predict failure mechanisms in solid-state batteries. The successful candidate will work on combining physics-based models with machine learning approaches to enable real-time data acquisition, analysis, and prediction. The project seeks to improve the understanding of degradation and failure processes, ultimately contributing to safer and more efficient battery technologies.
The doctoral researcher will be responsible for designing and implementing AI models, conducting experimental investigations using advanced microscopy techniques, and analysing complex datasets. The role includes collaboration with academic supervisors and research teams, participation in training and development activities, and dissemination of findings through publications and conferences. The candidate will benefit from access to modern research facilities and an interdisciplinary research environment.
Eligibility Criteria
- A first-class or upper second-class Honours degree (or equivalent) in Physics, Materials Science, Engineering, Computer Science, or a related discipline
- A Master’s degree in a relevant field is desirable
- Demonstrated interest in interdisciplinary research combining AI and physical sciences
Required Expertise/Skills
- Strong background in machine learning, artificial intelligence, or data science
- Knowledge of physics, materials science, or electrochemistry
- Experience with programming languages such as Python or similar
- Familiarity with data analysis, modelling, and computational techniques
- Analytical and problem-solving skills with attention to detail
- Ability to work independently and collaboratively within a research team
- Good written and verbal communication skills in English
Salary Details
Fully funded PhD scholarship covering tuition fees and providing a stipend (details in line with university and funding body regulations)
Application Deadline
Not specified