|Salary:||£32,816 to £35,845 per annum (according to experience).|
|Placed On:||11th September 2019|
|Closes:||14th October 2019|
Location: Oxford Road, Manchester
Closing Date (DD-MM-YYYY): 14/10/2019
Faculty / Organisational Unit: Biology, Medicine & Health
Contract Duration: Available For 2 Years in the First Instance
The integrated structure of our Faculty enables a truly translational approach to biology, medicine and health - from pure discovery science through to clinical application and patient care. It also encourages collaborative working, enabling staff to deliver innovative, world-leading research that has a very real and positive impact on people’s lives, as well as high-quality education and training to over 11,000 undergraduate and postgraduate students.
One of the biggest outstanding problems in biology is how we can predict evolution. This project will combine methods from biophysics, synthetic and systems biology to study how the existing molecular mechanisms determine evolution. Understanding this relationship will allow us to predict the effects of mutations, and hence improve our ability to predict evolution.
This is particularly important when it comes to understanding and predicting the evolution of antibiotic resistance – one of the most important examples of how evolution affects human lives today, already causing over 25,000 deaths per year in the EU alone, in addition to dramatically extending hospital stays and increasing health care costs. In order to tackle this problem, we need to develop predictive approaches that will help us not only extend the usefulness of existing antibiotics, but also inform the development of longer-lasting novel drugs.
The aim of this project is to improve our ability to predict multi-drug resistance evolution by integrating mechanistic, biophysical and evolutionary models in order to understand how the existing molecular mechanisms in the cell determine evolution.
This project will develop a mechanistic model that aims to predict the effects of mutations in promoters and transcription factors that control the expression of multi-drug resistance pumps (AcrAB-TolC). This will allow us to understand how biophysical mechanisms determine the effects of mutations in transcription factors and promoters, and hence how they drive resistance evolution. The model will then serve as the foundation of performing evolutionary simulations in order to study the consequences of different antibiotic prescription regimes (e.g. altering usage periods of antibiotics, rotating between them, etc.).
Two posts are available on this project. This postdoc (computation/theory) will work together with an experimental postdoc, with the aim to produce one of the first predictive genotype-phenotype maps, and hence dramatically improve our ability to predict antibiotic resistance evolution from first principles.
This post is available for up to 2 years in the first instance. Further funding may be available dependent on the progress and evolution of the project.
The School is strongly committed to promoting equality and diversity, including the Athena SWAN charter for gender equality in higher education. The School holds a Silver Award which recognises their good practice in relation to gender; including flexible working arrangements, family-friendly policies, and support to allow staff achieve a good work-life balance. We particularly welcome applications from women for this post. All appointment will be made on merit. For further information, please visit: https://www.bmh.manchester.ac.uk/about/equality/.
Please note that we are unable to respond to enquiries, accept CVs or applications from Recruitment Agencies.
Enquiries about vacancy shortlisting and interviews:
Manager: Dr. Mato Lagator.
Tel: 0161 305 5766
Tel: 0161 275 4499
Tel: 0161 850 2004
This vacancy will close for applications at midnight on the closing date.
Type / Role: