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Discovering Equations from Data in Drug Discovery


Department of Engineering

Dr R Carvalho Applications accepted all year round Funded PhD Project (European/UK Students Only)
Durham United Kingdom Applied Mathematics Biomedical Engineering Control Systems Statistics

About the Project

The project will investigate methods to extract differential equations from data to predict drug performance in time. The studentship involves bringing together and extending methods from statistical learning and convex optimisation to develop rigorous and efficient tools for the automation of modelling in drug discovery.

A movie introducing the topic can be found here:

https://www.youtube.com/watch?v=gVcsVkY0mgc

The successful applicant will be working within the Durham Institute for Data Science.

Prospective candidates will be judged according to how well they meet

the following criteria:

· First class honours (or high 2.1) degree in the mathematical sciences, computer science, physics, engineering or a related field.

· Strong understanding of statistics.

· Ability to undertake scientific programming in R and Python.

· Excellent written and spoken communication skills in English.

In the first instance, interested candidates are encouraged to make an informal enquiry to Dr Rui Carvalho . To apply formally for this studentship you need to submit a cover letter highlighting what you can bring to the project, CV and the names of two academic referees. Applicants

will be required to submit a formal application using the online system found at https://www.dur.ac.uk/postgraduate/study/apply/.

The Engineering Department holds an Athena Swan Bronze award, highlighting its commitment to promoting women in Science, Engineering and Technology.


Funding Notes

The Studentship is fully funded for 3.5 years with a tax-free stipend at the EPSRC rate (£15,285 for 2020/21). Full funding is only available to UK, or EU nationals with pre-settled or settled status; non-UK/EU nationals can apply but would only receive a partial contribution towards the tuition fees.
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