The Prob_AI Hub at the University of Bristol aims to develop world-leading, mathematically principled, scalable, and uncertainty-aware AI algorithms by bringing together researchers across disciplines. This role specifically focuses on advancing conditional simulation from diffusion models using Sequential Monte Carlo and Markov chain Monte Carlo methodology.
Requirements
- 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.
Responsibilities
- 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
Other
- Contract type: Open ended with fixed funding for 12 months or until January 31 2029, whichever is earlier.
- This is a full-time position, though we will consider applicants requesting part-time or other flexible working arrangements.
- Work pattern: Full time/35 hours per week.
- Grade: I/Pathway 2.
- Salary: £39,906 - £44,746 per annum.
