A Machine Learning Framework for Protein Interaction Prediction
- Self-funded PhD students only
- Number of awards: 1
- Deadline: Ongoing
- Supervisors: Contact Dr He Wang to discuss this project, and other potential funding opportunities, further informally.
The protein interactions in cells in the human body have a decisive impact on health, performance and disease treatment. Being able to model and predict such interactions will greatly enhance our abilities to improve health, to understand how certain diseases occur and to design new drugs. Whilst in recent years the data about the interactions of proteins with molecules and with other proteins in cells have increased significantly, it remains challenging to study these interactions for a large number of proteins.
The PhD project will use machine learning (ML) to model the interactions of proteins with molecules that are found in their environment e.g. lipids. The student will use protein structures from the Protein Data Bank and molecular simulations to identify regions of interactions. Then, ML approaches will be developed to learn the interactions, to identify patterns in such interactions and to provide predictions for the interactions of other proteins.
This project aims to combine cutting edge computational methodologies (artificial intelligence/ML and molecular simulations) to improve our ability to predict protein interactions. Given the rapid growth of the data of proteins and their interactions, this research is timely in utilising the cutting-edge AI technologies for a better understanding of protein interactions.
You must have achieved a bachelor degree with a 2:1 (hons), or equivalent, or a good performance in a Masters level course in a relevant subject. We also recognise relevant industrial and academic experience.
How to apply
Formal applications for research degree study should be made online through the university's website. Please state clearly in the research information second that the PhD you wish to be considered for is 'Artificial intelligence approaches to biological interactions between proteins and membranes' as well as Dr He Wang as your proposed supervisor.
If English is not your first language, you must provide evidence that you meet the University's minimum English Language requirements.
We welcome scholarship applications from all suitably-qualified candidates, but UK black and minority ethnic (BME) researchers are currently under-represented in our Postgraduate Research community, and we would therefore particularly encourage applications from UK BME candidates. All scholarships will be awarded on the basis of merit.
If you require any further information please contact the Graduate School Office
e: firstname.lastname@example.org, t: +44 (0)113 343 8000.