Research Associate / Senior Research Associate in Machine Learning
University of Bristol - School of Physiology, Pharmacology and Neuroscience, Somerset, MA, United States
Role
Are you experienced in NMR spectroscopy, applied to chemical structure determination? We invite you to undertake postdoctoral research in the group of Professor Craig Butts. The role involves developing and applying workflows for elucidation of 3D chemical structures based on NMR spectroscopic data, funded by an EPSRC programme in collaboration with Professor Andre Cobb at Kings College London. You will lead a programme of computation and experimental measurement of NMR data, liaise with our machine learning and data science teams to explore new frontiers in multi‑modal automated structure determination, and assist Professor Butts in mentoring the research group, coordinating day‑to‑day activities, and supporting postgraduate and undergraduate researchers.
Responsibilities
Develop and apply NMR experimental methods for determining 3D molecular structures
Conduct computational studies of 3D structures to compare with experimental NMR data
Work with machine learning specialists to develop experimental test sets for their AI tools for 3D molecular structure elucidation, especially synthetic catalysts or natural products of unknown conformation and constitution
Design and help prepare manuscripts for the experimental NMR sub‑group
Support the development of grant funding applications around 3D molecular structure elucidation
Qualifications
Hold a PhD (or be in final stages of preparing to submit for a PhD) in Chemistry and/or physical sciences
Have experience in using advanced NMR tools, such as multi‑dimensional NMR for 3D structure determination
Have an understanding of chemistry/molecular structure
Enjoy collaboration across experimental, computational and data science domains
Contract Details
Contract type:
Open‑ended with funding until 31/12/2028
Work pattern:
Full‑time / 1 FTE
Grade:
Grade or J / Pathway 2
Salary:
£39,906 - £50,253 per annum
School/Unit:
School of Chemistry
Shift pattern:
35h /week
Advert will close at 23:59 UK time on 30/04/2026
#J-18808-Ljbffr
Are you experienced in NMR spectroscopy, applied to chemical structure determination? We invite you to undertake postdoctoral research in the group of Professor Craig Butts. The role involves developing and applying workflows for elucidation of 3D chemical structures based on NMR spectroscopic data, funded by an EPSRC programme in collaboration with Professor Andre Cobb at Kings College London. You will lead a programme of computation and experimental measurement of NMR data, liaise with our machine learning and data science teams to explore new frontiers in multi‑modal automated structure determination, and assist Professor Butts in mentoring the research group, coordinating day‑to‑day activities, and supporting postgraduate and undergraduate researchers.
Responsibilities
Develop and apply NMR experimental methods for determining 3D molecular structures
Conduct computational studies of 3D structures to compare with experimental NMR data
Work with machine learning specialists to develop experimental test sets for their AI tools for 3D molecular structure elucidation, especially synthetic catalysts or natural products of unknown conformation and constitution
Design and help prepare manuscripts for the experimental NMR sub‑group
Support the development of grant funding applications around 3D molecular structure elucidation
Qualifications
Hold a PhD (or be in final stages of preparing to submit for a PhD) in Chemistry and/or physical sciences
Have experience in using advanced NMR tools, such as multi‑dimensional NMR for 3D structure determination
Have an understanding of chemistry/molecular structure
Enjoy collaboration across experimental, computational and data science domains
Contract Details
Contract type:
Open‑ended with funding until 31/12/2028
Work pattern:
Full‑time / 1 FTE
Grade:
Grade or J / Pathway 2
Salary:
£39,906 - £50,253 per annum
School/Unit:
School of Chemistry
Shift pattern:
35h /week
Advert will close at 23:59 UK time on 30/04/2026
#J-18808-Ljbffr