PhD Opportunity -- Statistical Scalability for Streaming Data
Lancaster University is currently advertising a 3.5 year fully-funded PhD studentship to join the EPSRC-funded StatScale programme, to begin by 1st October 2017 or earlier (by mutual consent).
StatScale is an exciting, 6 year programme of research, developing the next generation of statistical methods for streaming data. This £2.8M EPSRC programme grant is a collaboration between both Lancaster University and the University of Cambridge, together with AstraZeneca, BT, the Office for National Statistics, Shell and the Yale PET Centre. Full details of the programme are available at https://www.statscale.org.
We seek applications from candidates with a very strong mathematics, or related undergraduate, background, who are motivated by the work of the StatScale programme. As a PhD student, you will be advised by Professors Idris Eckley and Paul Fearnhead, and will join a friendly and supportive team of researchers working on the StatScale programme.
Areas of research focus will centre on one of the following streaming data challenge areas:
· Heterogeneity;
· Model misspecification;
· Computational-Statistical Trade-offs.
Across all themes, research will focus on developing new methods that are relevant to, and will have impact on, modern data-streaming applications. Such methods would address challenges such as how do we make decisions that are robust to inevitable errors in our model for the data? Or how do we balance the competing objectives of statistical and computational efficiency?
Studentship Funding:
A full studentship is available for 3.5 years, covering fees plus maintenance grant of approximately £16,000 pa tax free for those who count as Home/EU students for the purposes of fees. Unfortunately, non-UK/EU applicants would need to provide funding to cover the difference between home/EU and overseas fee rates.
Academic Requirements:
A first-class degree, or masters degree (or equivalent) in an appropriate subject.
Deadline for applications:
Applications will be reviewed starting on 19th February 2018 until the position is filled. The studentship will start at a mutually agreed date, but ideally no later than October 2018.
Application process:
Please send a cover letter, CV and undergraduate/masters transcript(s), to [log in to unmask] The cover letter should clearly explain your motivation for applying for this specific studentship, and give an outline indication of which streaming data challenge area you would be interested in investigating
Further information
Applicants are strongly encouraged to contact one or more of the Lancaster project leaders before applying:
Idris Eckley: [log in to unmask] and Paul Fearnhead: p.fearnhead @lancaster.ac.uk.
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