The University of Bristol is seeking to develop machine learning methods applied to the elucidation of chemical structure, including 3-dimensionality (stereochemistry, conformation) and dynamics, based on spectroscopic data.
Requirements
- Have experience in developing machine learning tools for scientific research
- Have an understanding of chemistry/molecular structure
- Have experience in coding, managing software and data curation
Responsibilities
- Developing new machine learning approaches to identifying molecular structure from spectroscopic data, including generative approaches to structure elucidation.
- Maintaining and developing the Butts group’s core IMPRESSION software for prediction of spectroscopic properties, and build in structure elucidation functionality into this suite
- Working with chemists to apply the machine learning tools to elucidation of molecule structures, in particular synthetic or naturally-sourced polyketide natural products of unknown conformation and constitution.
- Designing and helping prepare manuscripts in Professor Butts’ machine learning sub-group.
- Supporting the development of grant funding applications around machine learning for structure elucidation.
Other
- You hold a PhD (or are in final stages of preparing to submit for a PhD) in a relevant topic to machine learning and/or physical sciences
- Have excellent communication skills to enable collaboration across physical sciences and machine learning
- helping Professor Butts mentor his research group, coordinate group day-to-day activities and provide support for post-graduate researchers who are mentoring undergraduate students.
- Contract type: Open ended with fixed funding until 31/07/2028
- Work pattern: Monday - Friday
