Fixed-term: The funds for this post are available for 1 year in the first instance.

Proteins are the fundamental building blocks of the human body. Prof. Knowles' research group has developed a wide range of experimental and computational methods to better understand and predict protein behaviour. A key focus has been on developing approaches that can probe biological systems in a high-throughput manner. The PDRA's role will involve utilising experimental data to gain new insights into biomolecular behaviour and their interactions. This goal encompasses developing new data analysis approaches for high-throughput single molecule measurements, building new machine learning models based on the generated data to augment experimental measurements and developing of biophysics-augmented machine learning models for designing proteins and biomolecules with desired properties and behaviour.

The successful candidate will have:

PhD in biophysics or bioinformatics, or in machine learning with a scientific focus Strong analytical skills and proficiency in quantitative analysis of large datasets Extensive expertise in either using state-of-the-art machine learning approaches (active learning, representation learning etc.) or employing computational chemistry and bioinformatics approaches for modelling biomolecular and protein behaviour Demonstrated research leadership, as demonstrated by a strong publication record across experimental and computational sciences or other types of collaborative projects Specific examples of exceptional problem-solving abilities and instances demonstrating the capability to work independently as well as within a team. Specific examples showcasing excellent communication skills and the ability to effectively collaborate within an interdisciplinary research team.

Inquiries about this post should be addressed to Echo Williamson

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.