The University of Bath is advertising a competitive PhD on physics-based battery models for next-generation battery management. UK and international applicants may compete for funding. The deadline is 29 November 2026. The expected start is 4 October 2027. Applicants should consider the research fit and financial conditions together before deciding whether to apply.
Research Focus
The work develops computationally efficient electrochemical models for embedded battery management. It investigates adaptive model hierarchies, parameter identification and degradation. Validation considers accuracy alongside memory and execution-time constraints. Read the project description as a starting point for identifying a question that interests you, rather than assuming that every possible method will appear in the eventual thesis.
Location and Academic Team
The university base is Bath, United Kingdom. The topic connects batteries and embedded systems. Mechanical Engineering hosts the opportunity. It belongs to the faculty’s studentship competition. Dr Hao Yuan is the named supervisor. Informal enquiries are encouraged.
Who Can Apply
Applicants need a first or 2:1 honours degree or international equivalent, with a master’s advantageous. Demonstrable PDE, electrochemical-modelling, parameter-identification, embedded-implementation and high-performance-computing experience is requested. Non-UK applicants not currently studying in the UK must meet the English requirement before the deadline. Check the current programme requirements for the precise qualifications and supporting documents needed. A relevant subject or an eligible nationality does not by itself guarantee admission or an award.
Funding and International Conditions
Competitive funding covers tuition, £1,000 annual training support and a stipend listed at £21,805 for 2026/27. Overseas awards are capped, and visa and Immigration Health Surcharge expenses must be met personally. The stated stipend does not confirm the 2027/28 rate. Review the written award terms before making financial commitments.
Exploring the Research Problem
For optional preparation, imagine a model that gives a detailed answer but takes too long for the task it is intended to support. Ask what information must be retained before choosing a simpler representation. Consider which comparison would reveal whether the faster version loses an important aspect of the behaviour. This is a hypothetical research exercise, not a specified embedded implementation, a project benchmark or an additional admissions assessment.
You could extend the example by considering a simplified model that performs well under some inputs but poorly under others. Explain what evidence would help define where it can reasonably be used and where a different representation is needed. Keep computational efficiency separate from a claim of scientific adequacy, since the two questions require different checks. A clear account of those limits can help explain your interest in engineering models without implying that a preliminary implementation is ready for deployment.
Presenting Evidence of Preparation
If you have completed a modelling or programming project, describe the question, your own contribution, the implementation and how you evaluated the result. Explain a concrete decision about numerical accuracy, computational resources or parameter estimation that influenced the outcome. Distinguish configuring a provided solver from modifying it or writing a separate implementation. Connect your existing experience to the advertised technical requirements and identify a realistic learning goal without presenting interest in a method as evidence that you have already mastered it.
If supporting materials are requested, make your individual contribution clear when discussing work completed with other people. Distinguish a class exercise, an unpublished report and a peer-reviewed research output instead of presenting them as equivalent achievements. Explain what your evidence can establish and what remained unresolved, including any limitation that would matter to the conclusion. Adapt these preparation suggestions to the actual application questions, since optional advice does not add requirements to the programme’s document checklist or guarantee a particular assessment outcome.
How to Apply
Use the current programme instructions to establish the submission route and complete supporting-document checklist. Review the exact project title and academic contacts wherever the form asks you to identify your research preference. An informal academic conversation can clarify fit, but it does not replace a formal application or constitute an admission or funding offer.
- View scholarship details and follow the linked institutional application instructions.
- Select the Mechanical Engineering PhD and University of Bath URSA funding.
- Identify the exact project and supervisor, observing the maximum of two project choices, and submit by 29 November 2026.
Before Submitting
Information was checked on 23 October 2026. Reconfirm the deadline and current terms before submission, particularly where your ability to enrol depends on receiving an international award. Keep a copy of the final form and any written clarification that materially affects your eligibility, financial expectations or decision to accept an offer.