Kent Business School PhD Studentship in Quantitative Finance, UK

Applications are invited for a full-time PhD studentship in the area of Quantitative Finance starting as soon as possible but no later than January 2011. The studentship will involve working on Numerical Techniques for Calibrating Market Price of Risk under the supervision of Professor Radu Tunaru. The project will involve applications using real-estate data, interest rate data and equity options data and it is covering both theoretical work and empirical work. The research is aiming at producing high-impact papers in top quality journals and also important recommendations to practitioners in the finance industry.
The PhD student will join the Business School at the University of Kent at Canterbury. Kent Business School is the business and management department of the University of Kent and has expertise in Management Science, Marketing, Management and Finance. Over the last five years the School has experienced a major shift in research culture and undergone considerable expansion appointing over 19 senior research-active academics. In the 2008 RAE, 55% of our research was classified as “world leading and internationally excellent” and the Business School leapt from the middle of the RAE table to the top third of all UK Business Schools.
The School has a fully dedicated staff of 57 academics with international expertise and research backgrounds from 20 countries. The School currently has nearly 80 research students of which over half are from the EU or UK. PhD students attend a rich and varied programme of research and business seminars and participation in a yearly Poster Competition.
The studentship covers Home/EU fees and provides a monthly stipend (approximately £13,500 p.a). The ideal candidate would normally be expected to hold a 2:1 or First class honours degree plus an MSc, or equivalently an upper 5-year undergraduate degree if coming from Europe, with a background in financial engineering, financial mathematical finance, operational research, mathematics, statistics, computer science or some other quantitative discipline relating to the project. Excellent written and verbal communication skills are essential. Knowledge of or experience in the use Matlab is highly desirable while other computer programming (preferably C/C++ or S-Plus) is highly appreciated. Experience with handling large datasets and working with econometric packages would also be useful. Applications will be assessed based on previous academic achievements and relevant skills.
How to Apply
Initial applications should be sent to Claire Baldock, Research Secretary, Kent Business School, University of Kent, Canterbury, Kent CT2 7PE, telephone 01227 823009, e-mail phdinfo@kent.ac.uk quoting ‘Tunaru PhD Studentship’ in the e-mail subject. Further details regarding the studentship are available through the web link below:
http://www.kent.ac.uk/kbs/programmes/research/opportunities/index.html
Applications should be sent electronically and include all of the following materials:
A cover letter or proposal explaining your specific interest in the research project, relevant training and skills appropriate to working on the project, and long-term career goals
A curriculum vitae (CV)
Official transcript(s) of your undergraduate/postgraduate degrees
Names and contact information of two references (one of which must be from an academic institution you have studied at) who can supply letters of support if short-listed for the position
If English is not your first language then evidence should be supplied that meets the minimum English language requirements (Click for details).
http://www.kent.ac.uk/studying/postgrad/international/english.html?tab=entry-requirements
Informal enquiries may be directed by email to:
Professor Radu Tunaru, Kent Business School, e-mail r.tunaru@kent.ac.uk
Completed applications should be received no later than: 31st October 2010
Further scholarship information and Application:
http://www.kent.ac.uk/kbs/documents/research/opportunities/0910-Radu-studentship-details.pdf