At a Glance
- Tasks: Develop a Gaussian Process emulator for advanced nuclear physics calculations.
- Company: Join a leading research team in nuclear physics and astrophysics.
- Benefits: Fully funded PhD with a competitive stipend and research opportunities.
- Other info: Open to UK nationals; starting October 2026 with potential for later dates.
- Why this job: Make groundbreaking contributions to our understanding of neutron-rich matter and nuclear interactions.
- Qualifications: First or upper second-class degree in Physics, Mathematics, or related field; quantum mechanics background required.
The predicted salary is between 18000 - 21000 € per year.
Nuclear energy-density functionals are among the most powerful theoretical tools for describing atomic nuclei and for connecting laboratory nuclear physics with the properties of dense matter in neutron stars. However, reliable predictions in regions where experimental data are scarce remain limited by uncertainties in model parameters, functional form, and the extrapolation of calibrated interactions to neutron-rich systems.
The central aim of this project is to develop a Gaussian Process emulator for computationally expensive Relativistic Hartree-Bogoliubov and Quasiparticle Random Phase Approximation calculations, whose direct use in Bayesian parameter estimation is currently computationally prohibitive. By providing a fast and statistically controlled surrogate for these calculations, the emulator will enable Bayesian analyses of relativistic nuclear functionals that are presently out of reach.
With the emulator in place, Bayesian inference will be used to constrain nuclear model parameters using finite-nucleus observables, including binding energies, charge radii, giant resonances, and parity-violating electron-scattering data. Particular attention will be paid to the isovector sector of the nuclear interaction, which governs neutron skins, the nuclear symmetry energy, and the equation of state of neutron-rich matter. The resulting posterior distributions will be propagated to neutron-star radii and tidal deformabilities, connecting nuclear-structure experiments with astrophysical observations within a common statistical framework.
By combining relativistic nuclear theory, Bayesian statistics, and statistical emulation, this project will provide a rigorous assessment of the predictive power of modern relativistic nuclear functionals and deliver new insights into the behaviour of dense neutron-rich matter.
Supervisors: Dr Esra Yuksel and Professor Paul Stevenson
Entry requirements: Open to UK nationals only. Starting in October 2026. Later start dates may be possible; please contact Dr Esra Yuksel once the deadline passes. You will need to meet the minimum entry requirements for our PhD programme. Applicants should have, or expect to obtain, a first or upper second-class UK honours degree (or equivalent) in Physics, Mathematics, or a closely related discipline. A background in quantum mechanics is essential. Experience in nuclear physics, statistical methods, or scientific programming (Python or equivalent) is desirable but not required.
How to apply: Applications should be submitted via the Physics PhD programme page. In place of a research proposal, you should upload a document stating the title of the project that you wish to apply for and the name of the relevant supervisor.
Funding: Fully and directly funded for this project only for 42 months by STFC/UKRI. UKRI standard stipend.
Enquiries: Contact Dr Esra Yuksel
PhD Studentship: Bayesian Analysis of Relativistic Nuclear Energy Density Functionals in Surrey employer: University of Surrey
As a leading institution in nuclear physics research, we offer an exceptional environment for PhD candidates to thrive. Our collaborative work culture fosters innovation and intellectual growth, while our fully funded studentship provides financial security and access to cutting-edge resources. Located in the UK, this role not only allows you to contribute to groundbreaking research but also offers opportunities for professional development and networking within the scientific community.
StudySmarter Expert Advice🤫
We think this is how you could land PhD Studentship: Bayesian Analysis of Relativistic Nuclear Energy Density Functionals in Surrey
✨Tip Number 1
Network like a pro! Reach out to your professors, colleagues, and anyone in the field. They might know about opportunities that aren't advertised yet. Plus, a personal recommendation can go a long way!
✨Tip Number 2
Prepare for interviews by practising common questions related to your field. Think about how your skills in quantum mechanics and statistical methods can shine through. We want you to show off your knowledge and passion!
✨Tip Number 3
Don’t forget to tailor your approach! When applying for this PhD studentship, highlight your relevant experience in nuclear physics or programming. Make it clear why you're the perfect fit for this project.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to follow the proper channels. Good luck!
We think you need these skills to ace PhD Studentship: Bayesian Analysis of Relativistic Nuclear Energy Density Functionals in Surrey
Some tips for your application 🫡
Get to Know the Project:Before you start writing, take some time to really understand the project. Familiarise yourself with the key concepts like Bayesian analysis and nuclear energy-density functionals. This will help you tailor your application to show how your background fits perfectly with what we’re looking for.
Show Off Your Skills:Make sure to highlight any relevant experience you have, especially in quantum mechanics or programming. Even if you don’t have direct experience in nuclear physics, showcasing your analytical skills and willingness to learn can make a big difference!
Be Clear and Concise:When writing your application, keep it clear and to the point. We want to see your passion and qualifications without wading through unnecessary fluff. Use straightforward language and structure your document well to make it easy for us to read.
Apply Through Our Website:Don’t forget to submit your application via the Physics PhD programme page! It’s the easiest way for us to receive your documents and ensures you’re considered for the position. Plus, it keeps everything organised on our end!
How to prepare for a job interview at University of Surrey
✨Know Your Stuff
Make sure you brush up on your knowledge of nuclear energy-density functionals and Bayesian analysis. Familiarise yourself with the key concepts mentioned in the job description, like Gaussian Process emulators and the Quasiparticle Random Phase Approximation. This will show that you're genuinely interested and well-prepared.
✨Showcase Relevant Skills
Even if you don't have direct experience in nuclear physics or statistical methods, highlight any relevant skills you possess. If you've done any scientific programming in Python or similar, be ready to discuss it. We want to see how your background in Physics or Mathematics can contribute to the project.
✨Ask Insightful Questions
Prepare some thoughtful questions about the project and its objectives. This could include inquiries about the specific challenges they face in Bayesian parameter estimation or how they envision the emulator impacting their research. It shows that you're engaged and thinking critically about the work.
✨Connect with the Supervisors
Since Dr Esra Yuksel and Professor Paul Stevenson are your potential supervisors, do a bit of research on their work. Mentioning their recent publications or projects during the interview can help establish a connection and demonstrate your enthusiasm for working under their guidance.
