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ALLSTAT  February 2018

ALLSTAT February 2018

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Subject:

FUNDED PhD POSITION: Hierarchical experiments and likelihood approximations at the University of Southampton

From:

Dave Woods <[log in to unmask]>

Reply-To:

Dave Woods <[log in to unmask]>

Date:

Thu, 22 Feb 2018 12:22:49 +0000

Content-Type:

text/plain

Parts/Attachments:

Parts/Attachments

text/plain (25 lines)

A PhD scholarship, fully funded at UK/EU level, is available at the University of Southampton within the Statistical Sciences Research Institute and Mathematical Sciences under the supervision of Professor Dave Woods and Dr Helen Ogden.

The position is open to applications from students who hold, or expect to soon obtain, distinction-level MSc or First-class MMath degrees (or equivalent).

The project will develop new statistical methods for statistical design, modelling and inference using systems and approximations available on at least two hierarchical scales.

Understanding and exploiting hierarchical differences in the accuracy and cost of systems and approximations across different (physical, computational) scales is an important topic in many areas of statistical research. In general, accuracy and cost will be inversely related, with economically or computationally expensive "evaluations" (physical observations or computational approximations) giving highly accurate results. However, project budgets will generally be insufficient to allow statistical modelling and inference to rely solely on results from these evaluations. Instead, use must be made of lower cost, but lower accuracy, evaluations, which will be available in much greater quantities. 

This unique project would allow a student to make contributions to both design of experiments and likelihood-based inference by developing generic methods to best combine data and approximations from different scales. Example problems include designing experiments across lab, pilot and manufacturing scales to understand and predict manufactured product performance in the pharmaceutical industry, and constructing likelihood approximations for nonlinear regression models combining analytic (e.g. Laplace) with computational (e.g. Monte Carlo) approximations to obtain statistically valid and efficient inferences.

The studentship is institutional support for an EPSRC grant on “Combining chemical robotics and statistical methods to discover complex functional products”, recently awarded to the Universities of Cambridge, Glasgow and Southampton. As such, the student will have the opportunity to interact with a multidisciplinary team of statisticians, chemists and chemical engineers, and also industrial partners.

Further details are available by contacting Professor Woods - email: [log in to unmask]; web: www.southampton.ac.uk/~davew; phone 02380 595117.

Applications should be submitted online at 

http://www.southampton.ac.uk/postgraduate/pgstudy/howdoiapplypg.html

There is no formal closing date, and applications will be considered on merit as they arrive.

You may leave the list at any time by sending the command

SIGNOFF allstat

to [log in to unmask], leaving the subject line blank.

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