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Post-Doctoral Research Associate in Computer Simulations of Protein Phase Separation and Aggregation

University of Cambridge

Cambridge

On-site

GBP 60,000 - 80,000

27 days ago

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Job summary

An established industry player is seeking a talented postdoctoral research associate to engage in groundbreaking computational research. This role focuses on predicting TDP-43 mutant phase separation, contributing to vital insights into motor neurone disease. You will collaborate with leading researchers and apply advanced modelling techniques to unravel complex biological systems. This position offers a unique opportunity to work at the intersection of computational and experimental science, making significant contributions to understanding and addressing critical health challenges. Join a dynamic team dedicated to innovation and scientific excellence, and help drive forward impactful research.

Qualifications

  • PhD in Physics, Chemistry, or related field required.
  • Experience in modelling and simulations of condensed-matter systems.

Responsibilities

  • Conduct computational research on TDP-43 mutant phase separation.
  • Collaborate with experimental scientists to link simulations to data.

Skills

Modelling and simulations of condensed-matter systems

Biomolecular phase transitions

Molecular dynamics simulations

Monte Carlo simulations

Good communication skills

Education

PhD in Physics

PhD in Chemistry

PhD in a closely related field

Job description

Fixed-term: The funds for this post are available for 2 years in the first instance.


We are seeking an ambitious and talented postdoctoral research associate to join our team to work on a computational project focused on predicting TDP-43 mutant phase separation and aggregation in the context of elucidating the molecular driving forces behind motor neurone disease. This project is part of a Discovery Network funded by the My Name'5 Doddie Foundation ['Dissecting a TDP-43 knock-in allelic series to yield diverse MND drug targets'].


The successful candidate will join research groups led by Dr Aleks Reinhardt in the Department of Chemistry and Prof. Rosana Collepardo-Guevara in the Departments of Chemistry and Genetics, University of Cambridge. Both groups focus on developing computational and statistical-mechanical approaches to model the physical properties of matter and their underlying molecular mechanisms, including in biological systems. The overarching Discovery Network spans King's College London, the University of Dundee, and the University of Cambridge.


TDP-43 dysfunction can arise from mutations affecting aggregation and phase separation. Proteins featuring low-complexity aromatic-rich kinked segments, like TDP-43, can form interprotein ß-sheets, which drive fibrillisation in condensates, resulting in amyloid-like fibrils. Hydrogen-bond co-operativity between disordered protein regions increases binding affinity between certain motifs over time, encouraging fibrillisation and rigidifying the interacting proteins. In this project, we will investigate this behaviour computationally to gain molecular-level insights into the multiple possible mechanisms of aggregation.


As part of the overarching Discovery Network, we will collaborate closely with our experimental colleagues. This will allow us to link simulations directly to experimental data in order to uncover the molecular mechanisms explaining why and how pathological mutations disrupt material properties of the condensates they form, both at equilibrium and dynamically, and use that molecular-level information to design strategies to overcome the pathological outcomes of such MND mutations.


Candidate should have (or be about to obtain) a PhD in Physics, Chemistry, or a closely related field, with a strong interest in biological systems. Experience in modelling and simulations of condensed-matter systems, ideally including biomolecular phase transitions. Experience in developing or applying coarse-grained models, polymer models, and/or in developing and applying molecular dynamics and/or Monte Carlo simulations to biomolecular systems or condensed-matter systems, and good communication skills, ideally including a track record of collaboration with experimental scientists.


Appointment at the Research Associate level is dependent on the award of a PhD. Those who have submitted but not yet received their PhD will be appointed at the Research Assistant level, which will be amended to Research Associate once the award of the PhD has been confirmed.


The starting date is flexible, but it would ideally be in the early summer of 2025.


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


Please ensure that you upload your Curriculum Vitae (CV), a covering letter, and include a publications list in the upload section of the online application. If you upload any additional documents that have not been requested, we will not be able to consider these as part of your application.


Informal enquiries can be addressed via email to Prof. Rosana Collepardo (rc597@cam.ac.uk) and Dr Aleks Reinhardt (ar732@cam.ac.uk).


Please quote reference MA45279 on your application and in any correspondence about this vacancy.


The Department holds an Athena SWAN silver award for women in Science, Technology, Engineering, Mathematics, and Medicine.


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.

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