BBSRC MRes/PhD Studentship Parameter Inference and Synthesis for Stochastic Biological Models

Reference Code: CB100

Name of the supervisors
Dr P Zuliani (Principal Investigator), School of Computing Science

Professor A Wipat, School of Computing Science and Centre for Bacterial Cell Biology

Dr L Hamoen, Institute for Cell and Molecular Biosciences

This studentship is sponsored by the Biotechnology and Biological Sciences Research Council (BBSRC) as part of the Doctoral Training Partnership (DTP).

Duration of the award
Four years (MRes Biosciences followed by a three-year PhD).

Project description
In this project we aim at making fundamental advances in parameter inference and parameter synthesis for stochastic models of biological systems. Parameter inference aims at finding model parameters (e.g., reaction rate constants) that fit experimental results, usually presented in the form of time-series data. In this project we will investigate a novel computational approach based on the cross-entropy. Parameter synthesis has a similar aim as parameter inference but, instead of experimental data, it uses high-level, formal specifications of model behaviour. In particular, we will investigate a new approach that combines decision procedures and verified numerical computation to establish with high precision whether (and eventually how) a model can satisfy design requirements. We will apply the developed techniques to analyse parameters of bacterial models.

This studentship provides a unique opportunity to perform interdisciplinary research of the highest calibre and potential impact.

Value of the award and eligibility
Depending on how you meet the BBSRC?s eligibility criteria, you may be entitled to a full or a partial award. A full award covers tuition fees at the UK/EU rate and an annual stipend of ?13,726 (2013/14). A partial award covers fees at the UK/EU rate only.

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Person specification
We are looking for a person with a strong mathematics background and with a keen interest in developing and applying computational techniques to complex biological settings, including wet-lab experiments. The successful candidate will have an excellent first degree in, for example, mathematics, computer science, physics, electrical engineering, or statistics. Knowledge of biology is not a prerequisite, since the successful applicant will enrol on an MRes degree at Newcastle University.

How to apply
You must apply through the University?s online postgraduate application form selecting ‘PhD Computer Science – Computing Science’ as the programme of study. Once you have selected the programme, please insert the studentship/partnership reference number CB100. Only mandatory fields need to be completed (no personal statement required) and a covering letter, CV and (if English is not your first language) a copy of your English language qualifications must be attached. The covering letter must state the title of the studentship, quote the reference number CB100 and state how your interests and experience relate to the project.

You should also send your covering letter and CV to Dr P Zuliani at [email protected].

Closing date for applications
prompt application is advised as this post is only available until a suitable candidate is appointed.

Further information
For further details, please contact:
Dr P Zuliani
E-mail: [email protected]
Telephone: +44 (0) 191 208 8064

For more information and to submit an application, please click ?Apply? below.

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