Description of Postdoctoral Research Associate in Data-Driven Modelling of Collective Cell Behaviour
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Postdoctoral Research Associate in Data-Driven Modelling of Collective Cell Behaviour
further particulars: 171577_JobDescription_PDRA_Baker
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comment: We invite applications for an outstanding postdoctoral research associate in data-driven modelling of collective cell behaviour to work with Professor Ruth Baker at the Mathematical Institute, University of Oxford. This is a 36-month, fixed-term position, funded by the Simons Foundation. The start-date for this position is flexible, but September-November 2024 is preferred. The project will focus on combining theoretical and computational approaches (including machine learning) to understand fundamental aspects of collective cell behaviours. Examples of topics studied in the Baker group include collective migration driven by phenotypic heterogeneity, electrotaxis, fibrosis, and cell cycle regulation. The project will involve working closely with experimental collaborators of the Baker Group. The research undertaken in this role will be carried out under the Simons Foundation Grant “Simons Investigator Award” (MP-SIP-00001828). The postdoctoral researcher will be expected to conduct research both independently and collaboratively with other members of the group at Oxford and elsewhere. They are also expected to provide informal mentorship of doctoral students in the group. Candidates should have strong training in cross-disciplinary applied mathematics, with a demonstrated interest in biology, and experience in machine learning approaches is a plus. We proudly hold a departmental Athena SWAN Silver Award and an institutional Race Equality Charter Bronze Award, which guide our progress towards advancing racial and gender equality. As part of our strategic aim to improve staff equality and diversity, we would particularly welcome applications from women and BME candidates, who are currently under-represented in positions of this type within the department. Please direct informal enquiries to the Recruitment Coordinator (email: recruitment@maths.ox.ac.uk), quoting vacancy reference 171577. Applicants will be selected for interview purely based on their ability to satisf…
application closing date: 2024-04-15T12:00:00+01:00
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value: MATHEMATICAL INSTITUTE ANDREW WILES BUILDING Job Description and Selection Criteria Job title Postdoctoral research associate in data-driven modelling of collective cell behaviour Division Mathematical, Physical and Life Sciences Department Mathematical Institute Location Andrew Wiles Building, Radcliffe Observatory Quarter, Woodstock Road, Oxford, OX2 6GG. Grade and salary Grade 7: £38,205 – £44,263 per annum Hours Full time Contract type Fixed-term (24 months, with further extension possible) Reporting to Professor Ruth Baker Vacancy reference 171577 This is a full-time position that cannot be held concurrently with any other substantive post without the explicit permission of the Head of Department. Additional information This post is funded by the Simons Foundation. (PLEASE NOTE: Applicants are responsible for contacting their referees and making sure that their letters are received by the closing date) Research topic Developing and analysing new mathematical models of collective cell behaviour using data-driven approaches to model construction. Principal Investigator Professor Ruth Baker Project team The PDRA will work within the Baker Group, part of the Wolfson Centre for Mathematical Biology at the Mathematical Institute. Funding partner This project is funded by the Simons Foundation Research Group Mathematical Biology The role We invite applications for an outstanding postdoctoral research associate in data-driven modelling of collective cell behaviour to work with Professor Ruth Baker at the Mathematical Institute, University of Oxford. This is a 36-month, fixed-term position, funded by the Simons Foundation. The start-date for this position is flexible, but September-November 2024 is preferred. The project will focus on combining theoretical and computational approaches (including machine learning) to understand fundamental aspects of collective cell behaviours. Examples of topics studied in the Baker group include collective migration driven by phenotypi…
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