Computational Statistics

Potential PhD projects in this area include:

• Projected regression for large-p-large-n data (Supervisor: Chenlei Leng)
• Aggregating multiple estimates in Monte Carlo integration (Supervisor: Christian Robert)
• Folding Markov chains for higher efficiency (Supervisors: Christian Robert & Gareth Roberts)
• Understanding intrinsically disordered proteins through Bayesian computation (Supervisor: David Wild)
• Machine learning algorithms for non-stationary spatio-temporal inference (Supervisor: Theo Damoulas)
• Dividing and Conquering with SMC (Supervisor: Adam Johansen)
• Beyond the Bootstrap (Supervisor: Adam Johansen)