Research Associate

This role will undertake postdoctoral research in the group of Professor Craig Butts, developing machine learning methods applied to elucidation of chemical structure, including 3-dimensionality (stereochemistry, conformation) and dynamics, on the basis of quantum chemical computed or experimental spectroscopic data. This forms part of a large EPSRC-funded program of research ‘Automated Synthesis and Structure Elucidation of Polyketide Natural Products’ and will include working with synthetic chemists in the group of Varinder Aggarwal to test machine learning systems against challenging real world examples. The role holder will also be responsible for helping Professor Butts mentor his research group, coordinate group day-to-day activities and offer support for post-graduate researchers who are mentoring undergraduate students.

• 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.

• A PhD (or in final stages of preparing to submit for a PhD) in a relevant topic to machine learning and/or physical sciences.
• Experience in developing machine learning tools for scientific research
• Understanding of chemistry/molecular structure
• Experience in coding, managing software and data curation
• Excellent communication skills to enable collaboration across physical sciences and machine learning

Contract type: Open ended with fixed funding until 30/11/2025

Work pattern: 35 hours per week

Grade: I/pathway 2

Salary: £37,099 - £41,732 per annum

School/Unit: School of Chemistry

This advert will close at 23:59 GMT on 24/01/2024

Interviews are anticipated to take place shortly after the closing date.

For informal queries, please contact: Craig Butts - [email protected]  

We recently launched our strategy  to 2030 tying together our mission, vision and values.

The University of Bristol aims to be a place where everyone feels able to be themselves and do their best in an inclusive working environment where all colleagues can thrive and reach their full potential. We want to attract, develop, and retain individuals with different experiences, backgrounds and perspectives – particularly people of colour, LGBT+ and disabled people - because diversity of people and ideas remains integral to our excellence as a global civic institution.

This role will undertake postdoctoral research in the group of Professor Craig Butts, developing machine learning methods applied to elucidation of chemical structure, including 3-dimensionality (stereochemistry, conformation) and dynamics, on the basis of quantum chemical computed or experimental spectroscopic data. This forms part of a large EPSRC-funded program of research ‘Automated Synthesis and Structure Elucidation of Polyketide Natural Products’ and will include working with synthetic chemists in the group of Varinder Aggarwal to test machine learning systems against challenging real world examples. The role holder will also be responsible for helping Professor Butts mentor his research group, coordinate group day-to-day activities and offer support for post-graduate researchers who are mentoring undergraduate students.

• 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.

• A PhD (or in final stages of preparing to submit for a PhD) in a relevant topic to machine learning and/or physical sciences.
• Experience in developing machine learning tools for scientific research
• Understanding of chemistry/molecular structure
• Experience in coding, managing software and data curation
• Excellent communication skills to enable collaboration across physical sciences and machine learning

Contract type: Open ended with fixed funding until 30/11/2025

Work pattern: 35 hours per week

Grade: I/pathway 2

Salary: £37,099 - £41,732 per annum

School/Unit: School of Chemistry

This advert will close at 23:59 GMT on 24/01/2024

Interviews are anticipated to take place shortly after the closing date.

For informal queries, please contact: Craig Butts - [email protected]  

We recently launched our strategy  to 2030 tying together our mission, vision and values.

The University of Bristol aims to be a place where everyone feels able to be themselves and do their best in an inclusive working environment where all colleagues can thrive and reach their full potential. We want to attract, develop, and retain individuals with different experiences, backgrounds and perspectives – particularly people of colour, LGBT+ and disabled people - because diversity of people and ideas remains integral to our excellence as a global civic institution.