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Funded Postdoc position; in Computational Biology; at Department of Computational and Systems Biology at the John Innes Centre; in UK


Postdoctoral Researchers in Computational Biology

John Innes Centre, Norwich

Location: Norwich
Salary: £31,250 to £38,100 per annum depending on qualifications and experience
Hours: Full Time
Contract Type: Fixed-Term/Contract


Placed on: 15th September 2017
Closes: 27th October 2017
Job Ref: 1003336

Applications are invited for two Postdoctoral Researchers to join the group of Prof Martin Howard in the Department of Computational and Systems Biology at the John Innes Centre (JIC).


The Howard group mathematically models biological systems at the cellular level. Our approach is to construct simple models that can nevertheless make surprising and counter-intuitive predictions to be tested experimentally. The group’s approach is highly interdisciplinary, and relies extensively on techniques from statistical physics and applied mathematics, as well as on close collaboration with experimental groups. The group regularly publishes in the most prominent multidisciplinary journals, with recent papers in Science, Cell Systems, eLife and PNAS.

Several previous members of the Howard group now hold independent faculty positions of their own, including in Amsterdam, Singapore, Munich and Oxford.

The Roles:

The aim of the first project is to use mathematical modelling to understand quantitative transcriptional regulation in cases controlled by antisense transcription. These efforts will be focused on an environmentally controlled gene FLC, which is already known to be antisense regulated. The successful candidate will aim to understand how antisense-mediated regulation can control FLC expression in warm temperature conditions in a fundamentally analogue way, where expression can be tuned up or down like a molecular dimmer switch.

The second position focuses on the dynamics of DNA methylation, a key epigenetic regulator of gene expression. The successful candidate will work on a project supported by the European Research Council to achieve a quantitative understanding of how nucleosomes, linker histones, and other chromatin components influence the accurate inheritance of DNA methylation patterns. The project aims to predict the existence and function of new factors that regulate DNA methylation maintenance.

In both cases, approaches will include spatiotemporal stochastic modelling, as well as analytic calculations. State of the art, single cell experimental data will be available from our collaborators to help develop and parameterise the models. Both projects will give the successful candidates an opportunity to work on fundamental biological processes in a truly interdisciplinary environment, with seamless collaboration with experimentalists.

The Ideal Candidates:

The ideal candidates will possess a PhD in Theoretical Physics, Bio-Mathematics or Computational Biology. They will possess a strong interest in biological problems and have achieved demonstrable scientific success in previous roles. Prior experience of biological modelling is desirable but not essential.

Additional information:

Salary on appointment will be within the range £31,250 to £38,100 per annum depending on qualifications and experience.  Both posts are full time and for a period of 3 years.

For further information and details of how to apply, please visit our web site or contact the Human Resources team on 01603 450462 or  quoting reference 1003336.

As a Disability Confident employer, we guarantee to offer an interview to all disabled applicants who meet the essential criteria for this vacancy. The John Innes Centre is also proud to hold a Silver Award from Athena SWAN and is a member of Stonewall’s Diversity Champions programme.

Shortlisting will begin on Friday 13th October but applications will continue to be accepted until the positions are filled.

The John Innes Centre is a registered charity (No. 223852) grant-aided by the Biotechnology and Biological Sciences Research Council and is an Equal Opportunities Employer.

Deadline: October 27, 2017.

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