PhD studentships in “Efficient and Reliable Probabilistic Machine Learning”

Two fully funded PhD positions to work with Dr Antonio Vergari in the School of Informatics at the University of Edinburgh, on projects in the research areas of Probabilistic Machine Learning, Neuro-Symbolic AI and Deep Generative Models.

PhD candidates will research the methodological foundations for a new generation of probabilistic models and programs that come with guarantees while being efficient. Possible topics include but are not limited to: i) expanding the theoretical boundaries of reliable probabilistic inference and unifying modern probabilistic formalisms ii) designing modular algorithms for complex probabilistic inference with guarantees in the presence of constraints and heterogeneous data iii) devising novel and efficient algorithms to learn probabilistic models and programs from data, iv) complex reasoning with deep generative models.

Candidate’s profile

  • A strong background in math, statistics probability and programming, as demonstrated by grades in relevant courses or by previously taken projects.
  • Proficiency with modern deep learning frameworks such as pytorch, jax
  • A Bachelor’s Hons degree (classification 2.1 or above, or equivalent) and/or Master’s degree in Computer Science, Mathematics, Physics or Engineering.
  • Proficiency in English (both oral and written)
  • Previous experience in probabilistic modeling and programming is desirable.

Studentship and eligibility

The studentship covers:

  • Full time PhD tuition fees for a student with a Home fee status (£4,712 per annum) or overseas fee status (£29,700 per annum)
  • A tax-free stipend of GBP £18,622 per year for 3.5 years
  • Additional programme costs of £1000 per year.

Application Information

Applicants should apply via the University’s admissions portal (EUCLID) and apply for the following programme: Informatics: ANC: Machine Learning, Computational Neuroscience, Computational Biology with a start date of October 2023 (Home applicants) or January 2024 (international applicants).

Applicants should state “Efficient and reliable probabilistic machine learning” and the research supervisor (Dr Antonio Vergari) in their application.

Complete applications submitted by 9 July 2023 will receive full consideration; after that date applications will be considered until the position is filled. The start date is October 2023 or January 2024 but later start dates can be considered.

Applicants must submit:

  • All degree transcripts and certificates (and certified translations if applicable).
  • Evidence of English Language capability.
  • A short research proposal highlighting how previous experience and current interests match this position (max 2 pages). This is perhaps the most crucial document, take your time to carefully write it!
  • A full CV and cover letter (max 1 page).
  • Two references (it is the applicant’s responsibility to ensure reference letters are received before the deadline).

Only complete applications will be considered.


The School of Informatics is one of the largest in Europe and currently the top Informatics institute in the UK for research power, with 40% of its research outputs considered world-leading (top grade). The University of Edinburgh is constantly ranked among the world’s top universities and is a highly international environment with several centres of excellence.

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