or
Looking to list your PhD opportunities? Log in here.
Many projects in Engineering and Computer Science involve global multivariate optimisation. Classical methods include genetic algorithms, simulated annealing and particle filters. One way to think about global optimization is as density estimation, where Markov chain Monte Carlo methods attempt to learn the properties of an optimisation surface as if it were a probability distribution. This project is about doing that surface characterisation in a new way. The idea is to begin local ascent algorithms from multiple start points and then use the information about distance and directions travelled in each case to estimate maxima density. From this, we would make principled choices about how many starts to attempt and stopping criteria for a high probability of finding the global maximum.
Entry requirements:
Candidates should have (or expect to obtain) a minimum of a UK upper second class honours degree (2.1) or equivalent in Electronic and Electrical Engineering, Physics, Computer Science, Mathematics, Music Technology or a closely related subject.
How to apply:
Applicants should apply via the University’s online application system at https://www.york.ac.uk/study/postgraduate-research/apply/. Please read the application guidance first so that you understand the various steps in the application process.
Based on your current searches we recommend the following search filters.
Check out our other PhDs in York, United Kingdom
Start a New search with our database of over 4,000 PhDs
Based on your current search criteria we thought you might be interested in these.
Stochastic response characterisation and reliability driven optimisation of floating wind turbines
University of Aberdeen
EPSRC supported EngD project. Design and Optimisation of Surface Actives for Sustainable Hygiene Products
University of Birmingham
Microstructural and surface integrity in machining of specialist composite materials for next generation aero-engine applications - (ENG 1317X2)
University of Nottingham