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Position: PhD Studentships in Statistical Science
Institution: University College London
Department: Statistical Science
Location: London, United Kingdom
Duties: The following projects are available: Combining randomised control trial data with observational studies; Computationally-intensive machine learning for causal inference; Data assimilation and calibration of systems of computer models; Isomorphisms of random systems; Large scale modelling of trajectory data; Modeling of contagion effects in financial markets; Robust and efficient Bayesian computation; Stochastic models in genetics: using DNA sequence data to learn about population divergence and speciation; Validity of graphical causal modeling
Requirements: 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
   
Text: PhD Studentships in Statistical Science, - Ref:1859958 Click here to go back to search results UCL Department / Division Statistical Science Location of position London Duration of Studentship 4 years Stipend £17,432 per annum plus UK/EU Fees Vacancy Information Applications are invited for two PhD funding opportunities to conduct research in a branch of probability or statistics based in the UCL Department of Statistical Science, commencing in September 2020. The studentships will be 4 years in duration (or 6 years for part-time candidates) and cover tuition fees at the UK/EU rate, an annual stipend (£17,432 in 2020/21) 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. Studentship Description The following projects are available (outline descriptions are provided in a separate pdf document ). Combining randomised control trial data with observational studies Computationally-intensive machine learning for causal inference Data assimilation and calibration of systems of computer models Isomorphisms of random systems Large scale modelling of trajectory data Modeling of contagion effects in financial markets Robust and efficient Bayesian computation Stochastic models in genetics: using DNA sequence data to learn about population divergence and speciation Validity of graphical causal modeling 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, candidates may propose their own topics, provided that they have 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 Bachelors degree, or a Masters 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 . Eligibility All new candidates should apply for the Research Degree: Statistical Science (RRDSTASING01) by completing the online form and, in addition (and very importantly), send a separate covering letter making their case for the funding. The covering letter should be sent to Ms Marina Lewis at the email address below. Candidates already in receipt of an offer of admission need only send the covering letter. Applications will be considered on a rolling basis, the first batch on 28 February, 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. Contact name Ms Marina Lewis Contact details stats.pgr-admissions@ucl.ac.uk UCL Taking Action for Equality Closing Date 31 Mar 2020 Studentship Start Date 28 Sep 2020
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