Prospective PhD students and PostDoc researchers
Opportunities for PhD and PostDoc positions
Fully funded 4y studentships at the Warwick Centre for Doctoral Training in Mathematics and Statistics
The studentships are for a period of 4 years with starting date October 2019. Funding includes a stipend at UKRI rates and tuition fees at UK/EU rates. Details are provided at the Centre for Doctoral Training in Mathematics and Statistics pages.
EPSRC DTA studentships and Department of Statistics PhD bursaries at University of Warwick
Details are provided on the PhD application guidance pages of the Department of Statistics at University of Warwick.
October 2018 (applications are now closed)
Fully funded doctoral studentships at the Alan Turing Institute
Details on the application process are provided at the Alan Turing Institute wepbpages.
I am actively looking for PhD students and PostDocs to join my group. Feel free to contact me directly if you are interested in doing a PhD with me as your supervisor or if you are interested in doing post-doctoral work with me. Please include a CV, a brief research statement, and an outline of the reasons you want to work with me.
Information about doing a PhD in the Department of Statistics at University of Warwick, the application process and funding opportunities can be found at the Department of Statistics webpages. You may also consider applying for a Doctoral Studentship under my supervision at the Alan Turing Institute. Calls for applications and application details usually appear here but I will also be posting them above.
Apart from posts that I may be advertising occasionally, there is typically a range of funding opportunities that can be explored for post-doctoral appointments, both ad-hoc and by submitting proposals to research councils. If you are interested in the latter, the earlier that you contact me before your intended start date the better.
Topics of interest
I am currently especially keen in working with PhD students and PostDocs on aspects of the following topics:
- Asymptotic methods for improved inference in modern modelling scenarios
(e.g. high-dimensional models, functional regression, etc.)
- Dynamic and scalable estimation and inference in regression modelling
- Missingness in regression settings and misclassification
- Data-analytic pipelines and statistical software
- Statistical applications
(of the kind that require non-trivial modelling and can drive developments in methodology)
The above list is in no way exhaustive and I am happy to discuss any suggestions and ideas you may have. Check out also my research and software pages for broad areas that I am currently interested in and my recent research outputs. Take a look also below at what the current PhD students in my group are working on.
Current PhD students
Below is a list of current PhD students working in my group and short descriptions of what they are working on.
|Zhenzheng Hu||2017-||jointly with Ioanna Manolopoulou|
|Petya Kindalova||2016-||jointly with Thomas Nichols|
|Santhosh Narayanan||2016-||jointly with Petros Dellaportas|
|Zhongzhen Wang||2016-||jointly with Petros Dellaportas|
Zhengzheng Hu is researching methods for the statistical modelling of binary data that can formally account for and model potential misclassification.
Petya Kindalova is developing statistical methodology for the modelling of brain lesions from MRI data. A particular aim of her work is to develop methods that not only possess statistical optimality guarantees but are also scalable in terms of computing and memory requirements.
Santhosh Narayanan is focusing on a new framework for modelling with stochastic processes and the associated procedures to infer the dynamics of event sequences and predict both the time and the type of the next event. He is looking at applications in team sports and cyber-security.
Zhongzhen Wang is researching ways of inferring significant lags for categorical time series data and forecasting using Bayesian non-parametric methodology with flexible statistical models.
Asma Saleh is investigating the effects that estimation bias and its correction have on inference from statistical models that are used in everyday statistical practice. She is primarily focusing on settings where the most realistic assumptions on information growth about the model parameters are beyond the ones typically encountered in textbooks.
Alkeos Tsokos is researching inference and prediction methods when smooth components are used for more realistic modelling (e.g. generalised additive models, functional regression and structural equations models). He is primarily looking at applications in cycling.
Completed PhD students
Below is a list of completed PhD students, including students from other institutions who spend a significant part of their PhD working with me.
|Claudia Di Caterina||2014-2015||visiting PhD student | jointly with Nicola Sartori|
|Emmanouil Karimalis||2013-2014||visiting PhD student | jointly with Gareth W Peters|
Post-Doctoral Research Associates
Below is a list of post-doctoral research associates who are or have been working with me.
|Thomas Bartlett||2016 -||with Ricardo Silva | host advisory team|
|Gavin Whitaker||2016 - 2018||with Ricardo Silva | 2nd advisor|
|Hannah Frick||2015 - 2017|
More information on supervision of post-doctoral research associates, PhD students, and BSc/MSc project students can be found in my CV.