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PhD Studentships and Teaching Assistantships in Statistical Science

University College London - Statistical Science

Qualification Type: PhD
Location: London
Funding for: UK Students, EU Students, International Students
Funding amount: £17,009 per annum plus UK/EU Fees
Hours: Full Time, Part Time
Placed On: 21st February 2019
Closes: 30th April 2019
Reference: 1795365

Start Date: September 2019

Applications are invited for a number of PhD funding opportunities (two EPSRC studentships and two internally-funded Teaching Assistantships) to conduct research in a branch of probability or statistics based in the UCL Department of Statistical Science, commencing in September 2019.

The EPSRC studentships will be 4 years in duration (or 6 years for part-time candidates) and cover tuition fees, an annual stipend (£17,009 in 2019/20) and a small allowance for consumables. To be eligible for a full award, applicants must normally have no restrictions on how long they can stay in the UK and have been ordinarily resident in the UK for 3 years prior to the start of the studentship. Further details concerning the regulations on student eligibility are available on the EPSRC website.

The Teaching Assistantships will be 3.5 years in duration (or 5.5 years for part-time candidates) and cover tuition fees (one at the UK/EU rate and one up to the overseas rate), an annual stipend (£17,009 in 2019/20) and a small allowance for consumables. The Teaching Assistants will spend 6 months of their time teaching (spread across the 3.5 years) and devote the remainder to undertaking their research.

Studentship Information

The following projects are available (outline descriptions are provided in a separate pdf document).

  • Analysis of Raman images for early detection of cancer
  • Bayesian functional data analysis with an application to modelling the effect of training on performance in sport
  • Causal inference in sequential off-policy scenarios, with applications to the digital economy
  • Comparing hospital performance and detecting outliers
  • Economic modelling applications of reinforcement learning techniques
  • From massive to individualised path planning analysis
  • Modeling of contagion effects in financial markets
  • Risk predictions models for survival outcomes with time updated predictors
  • Stochastic models in genetics: using DNA sequence data to learn about population divergence and speciation
  • Structured high-dimensional changepoint estimation

Candidates should explain in their covering letter which of these projects is of interest to them (please select at least one and up to three projects, in ranked order of preference). Alternatively, a candidate may propose their own topic, provided that it has already been discussed with a prospective supervisor in the department.

Person Specification

The requirement for admission to the MPhil/PhD in Statistical Science is a 1st class or high upper 2nd class Bachelor’s degree, or a Master’s degree with merit or distinction, in Mathematics, Statistics, Computer Science, or a related quantitative discipline. Overseas qualifications of an equivalent standard are also acceptable. Further details can be found on the Departmental website.

How to Apply

For details on how to apply, please visit:

Applications will be considered on a rolling basis, the first batch on 07 April, until the studentships are filled (i.e. the below closing date represents only a final deadline). You are therefore advised to apply as soon as possible.

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