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Postdoctoral Research Associate in Numerical Simulations for Biomolecular Modelling

The University of Edinburgh - College of Science and Engineering - School of Mathematics

Location: Edinburgh
Salary: £40,497 to £48,149 per annum. Grade UE07
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 4th March 2025
Closes: 15th April 2025
Job Ref: 12195

Full time: 35 hours per week (100% FTE)

Fixed Term: for 24 months

We are looking for an outstanding candidate to work on project UNTauANGLE: Untangling the biophysics of tau aggregation through computational modelling, within the School of Mathematics at the prestigious University of Edinburgh, UK.

The Opportunity:

The aim of the project is to develop and implement a mathematical and numerical modelling framework to understand the fundamental physical processes underlying the dysfunction of the tau protein. The dysfunction of tau, which is tightly linked to a large class of dementias called tauopathies, includes the formation and runaway growth of multi-protein clumps that result in severe damage to neurons. There is still no effective treatment for tauopathies caused by excessive clumping of tau, largely due to an incomplete physical understanding of the molecular interactions and conditions in the neuron that dysregulate tau. The successful applicant, working closely with Dr. Luke Davis, will bring together coarse-grained “minimal” molecular modelling approaches, statistical physics, and high-throughput molecular dynamics computer simulations into a single tau-modelling framework. There is scope for a strong candidate to shape the research direction. The project is funded by the Wellcome Trust, through the Wellcome Accelerator Award (311948/Z/24/Z).

Candidates can make informal enquiries about this post by contacting Dr. Luke Davis (luke.davis@ed.ac.uk).

Your skills and attributes for success:

The appointee has (or soon to have obtained) a PhD in applied mathematics, theoretical biophysics, physics, mathematical biology, or a related discipline. We are particularly encouraging applicants with a strong background in statistical and computational physics, and those with research experience in the modelling of living and active matter. It is essential that you have a demonstrable ability to produce academic writing of the highest quality.

Specifically:

  • Excellent knowledge of statistical physics and biophysics.
  • Experience with molecular dynamics simulations.
  • Experience in the efficient running of code on high performance computers.
  • Strong coding skills in an object-oriented language.
  • Experience with simulation libraries (e.g. LAMMPS) would be highly beneficial.

Closing date: 15/04/2025 at 11:59 pm

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