Post-Doctoral Research Associate in Computer Simulations of Protein Phase Separation and Aggregation (Fixed Term)

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 focussed 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.

To apply online for this vacancy and to view further information about the role, please click the 'Apply' button above. 

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.

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

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