ACAD108414

University of Bristol; Bristol; On-site; GBP 30,000 - 42,000; Full time

Job summary

A leading UK university seeks a Post-Doctoral Research Associate to advance research in probabilistic AI within the Prob_AI Hub. The role involves theoretical research on conditional simulation using advanced Monte Carlo methods. Candidates should hold a relevant postgraduate degree and demonstrate strong expertise in statistical methods and academic writing. This position is available for a fixed term of 12 months, starting immediately, with opportunities to publish impactful research in collaboration with various academic and industrial partners.

Qualifications

• Conducts methodological and theoretical research on conditional simulation from diffusion models.
• Demonstrates ability to develop new methodology for AI methods.
• Engages with partner institutions and industrial project partners.

Responsibilities

• Support research to achieve the University of Bristol's aims within the Prob_AI Hub.
• Publish research findings in leading journals.
• Attend project meetings and workshops.

Skills

Expertise in Sequential Monte Carlo methods

Expertise in Markov chain Monte Carlo methods

Mathematical understanding of AI

Strong academic writing skills

Education

Postgraduate research degree in Mathematics, Statistics, or Machine Learning

Job description

We invite applications for a Post-Doctoral Research Associate position to join the Prob_AI Hub. The vision of the Prob_AI hub is to develop a world‑leading, diverse and UK‑wide research programme in probabilistic AI. The hub will develop the next generation of mathematically principled, scalable and uncertainty‑aware AI algorithms. This will be achieved through bringing together world‑leading researchers across Applied Mathematics, Computer Science, Probability and Statistics, who engage with a range of non‑academic partners. This particular role involves conducting methodological and theoretical research on conditional simulation from diffusion models using Sequential Monte Carlo and Markov chain Monte Carlo methodology. This Prob_AI Hub brings together research groups from the Universities of Lancaster, Bristol, Cambridge, Edinburgh, Manchester and Warwick. This position at Bristol is available immediately, for a fixed term of 12 months or until January 31 2029, whichever is earlier.

What will you be doing?

• Support and undertake research necessary to achieve the University of Bristol's aims within the Prob_AI Hub. Specifically for this project, this will involve conditional simulation of diffusion models using Sequential Monte Carlo and Markov chain Monte Carlo.
• Publish in leading machine learning, AI, statistical, mathematical, or appropriate application journals.
• Contribute to publications in these journals jointly with other members of the project.
• Engage with other partner institutions and industrial project partners.
• Attend project meetings, events, workshops, and conferences.
• Develop code that implements the methods developed to support reproducible research practice.
• A relevant postgraduate research degree in Mathematics, Statistics, Machine Learning, or a related discipline, or possess equivalent professional experience.
• An interest in developing a mathematical understanding of AI to enhance the reliability, interpretability, and uncertainty awareness of AI methods.
• Expertise in both Sequential and Markov chain Monte Carlo methods, and familiarity with conditional simulation using diffusion models.
• Technical and mathematical skills required for such research, regardless of prior AI experience.
• You can demonstrate the ability to develop new methodology or advance mathematical understanding.
• A demonstrated ability to produce academic writing of the highest publishable quality.