OxWaSP - Doctoral Training in Statistical Science for 21st Century Data-¬Intensive Environments and Large-¬Scale Models.
The Statistics Department - University of Oxford and the Statistics Department - University Of Warwick, supported by the EPSRC, will run a new Centre for Doctoral Training in the theory, methods and applications of Statistical Science for 21st Century data-¬intensive environments and large-¬scale models.
This is the first centre of its type in the world and will uniquely equip its students to work in an area of growing demand both in academia and industry.
Each year OxWaSP (the Oxford Warwick Statistics Programme) will recruit at least 5 students attached to Oxford on the Statistical Science (Centre for Doctoral Training) course, and at least 5 attached to Warwick. Each student is fully funded for four years and all students, including those attached to Warwick, spend the first year of research training in Oxford.
An exciting training programme is delivered by world-leading researchers in Statistical Methods and Computational Statistics from Oxford and Warwick.
There are funded opportunities for students to work with our leading industrial partners and to travel to an international summer placement in some of the strongest Statistics groups in the USA, Europe and Asia.
Applications are currently being accepted for the first intake of students who will start in October 2014. Applications should be received by the end of January with interviews taking place in February.
Students will have, or be expected to obtain, a First Class Honours degree or Master’s degree in a subject that contains strong Mathematics training and have had significant exposure to Statistics or machine learning. Students must be motivated to do research in Statistics for high dimensional data analysis or for high dimensional modelling and become a future leader in statistical methodology and computational statistics.
More details are available at the website http://www2.warwick.ac.uk/fac/sci/statistics/oxwasp and enquiries can be sent to This email address is being protected from spambots. You need JavaScript enabled to view it.
