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Research Associate in Mathematical Modelling

Posted by , on 10 May 2022

Location: Sainsbury Laboratory, University of Cambridge, Cambridge, UK

Closing Date: 29 May 2022

Applications are invited for a Post-doctoral Research Associate position in the group of Dr. Francois Nedelec at the Sainsbury Laboratory Cambridge University (SLCU), to carry out fundamental research in the field of mathematical modelling. The aim of the group is to build models to physically analyse emergent properties, given the known molecular components involved in these processes.

This research will focus on (1) plant morphogenesis or (2) chromosome segregation. Project (1) is funded by the Gatsby Charitable Fundation and is aimed principally to promote collaborations within the Sainsbury Laboratory or more widely with the plant research community. Project (2) is funded by the ERC Synergy project BIOMECANET which is a collaboration of the Nedelec group with the experimental working groups of Andrea Musacchio (MPI of Molecular Physiology, Dortmund, DE) and Thomas Surrey (CRG, Barcelona, SP).

BIOMECANET aims to reconstitute crucial aspects of cell division in vitro with purified components and realistically simulate these processes in the computer. The emphasis will be on i) the cell cycle, which is a dynamical reaction-diffusion system that controls the timing of key events during division and ii) the cytoskeleton which involves chemistry and intracellular mechanics of filaments, mostly microtubules. The overall aim is to integrate these two key pieces of machinery to reconstruct the processes of chromosome bi-orientation and segregation. The position is funded with the aim of integrating experimental data with models, and exciting possibilities for collaborations are offered with this project.

Applicants should have, or be close to obtaining a Ph.D. in computational biology, physics, applied mathematics, computer science or related field and have a proven track record of scientific publications. Prior experience in modelling of biological systems, or expertise in systems biology and/or theoretical biophysics, in general, would be advantageous. The successful applicant will have the opportunity to develop skills in mathematical modelling, advanced numerical simulations and data/image analysis.

Fully involved in the basic research in these areas whilst also writing up their research work for presentation and publication, the post holder will have the opportunity to assist in the supervision of student projects, and to engage in teaching if desired. Good and effective communication skills are essential (e.g. presentations, outreach activities).

Where a PhD has yet to be awarded the appointment will initially be made at Research Assistant level (Grade 5) and amended to Research Associate (Grade 7) upon the award of PhD.

The Laboratory provides a welcoming and collaborative environment with a wide-range of family-friendly benefits and development opportunities. More about the Sainsbury Laboratory and details of what the University offers to employees, can be found at: http://www.slcu.cam.ac.uk/.

Please ensure that you upload a copy of your full CV with publications list, a supporting statement and contact information of three referees

Fixed-term: The funding for this post is available until 31.1.2024 in the first instance.

Scientific enquiries apart from the formal application should be directed to Dr Francois Nedelec at Francois.Nedelec@slcu.cam.ac.uk.

Click the ‘Apply’ button below to register an account with our recruitment system (if you have not already) and apply online.

Please quote reference PT31139 on your application and in any correspondence about this vacancy.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.

Further information

Closing Date: 29 May 2022

Scientific fields: Computational and systems biology, Cell biology, Plant development

Model systems:

Duration: Fixed term

Minimum qualifications: Applicants should have, or be close to obtaining a Ph.D. in computational biology, physics, applied mathematics, computer science or related field and have a proven track record of scientific publications.

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