Research Fellow Full-time

Research Fellow

The main purpose of this position is to develop and assess deep learning tools to transform and analyse complex NMR data. Combining deep learning and NMR will allow for new and more sensitive methods. A second objective of the research is to develop reinforcement learning tools, which in turn develop optimised NMR methods (pulse sequences). The research includes both building AI strategies as well as developing optimal NMR pulse sequences.

Research Fellow – Appointment at Grade 7 is dependent upon having been awarded a PhD; if this is not the case, initial appointment will be at Grade 6B (salary £38,357 – £41,005 per annum) with payment at Grade 7 being backdated to the date of final submission of the PhD Thesis.

We will consider applications to work on a part-time, flexible and job share basis wherever possible. This role is NOT generally eligible for hybrid working, but requires on-site working.

This appointment is subject to UCL Terms and Conditions of Service for Research and Professional Services Staff. This appointment is subject to UCL Terms and Conditions of Service for Academic Staff.

The role is eligible for Skilled worker Visa cost reimbursement as well as covering the costs for a Certificate of Sponsorship.

You are most of all curious and ambitious and with a strong background in biomolecular NMR spectroscopy, artificial intelligence and scientific programming. You will hold, or be close to completing, a PhD in a relevant discipline and have a publication record demonstrating your ability to deliver original research.

You will have experience designing and implementing advanced NMR pulse sequences, particularly experiments used to investigate chemical exchange and protein dynamics, and practical knowledge of Bruker NMR spectrometers. You will also have substantial expertise in Python, including the development of software for analysing, visualising and interpreting NMR spectra. Experience building and training deep neural networks for the transformation or analysis of complex scientific datasets (ideally NMR) is essential, while knowledge of reinforcement learning would be advantageous.

You should be confident in analysing protein NMR spectra, including datasets used for chemical-shift assignment and the quantitative characterisation of conformational exchange. You will be able to discuss complex scientific findings clearly through publications, conference presentations and discussions with collaborators.

We are looking for someone who is intellectually curious and has a true drive for new discoveries. You will contribute positively to our geeky research environment, support students, maintain reproducible research practices, and manage deadlines effectively. A flexible, collegiate approach, commitment to research integrity is essential. You will pursue new ideas while truly enjoying the journey.

An exciting geeky research environment and a very supportive group of people.

As well as the exciting opportunities this role presents, we also offer some great benefits some of which are below:

• 41 Days holiday (27 days annual leave 8 bank holiday and 6 closure days)
• Additional 5 days' annual leave purchase scheme
• Defined benefit career average revalued earnings pension scheme (CARE)
• Cycle to work scheme and season ticket loan
• Immigration loan
• Relocation scheme for certain posts
• On-Site nursery
• On-site gym
• Enhanced maternity, paternity and adoption pay
• Employee assistance programme: Staff Support Service
• Discounted medical insurance

Our commitment to Equality, Diversity and Inclusion

As London's Global University, we know diversity fosters creativity and innovation, and we want our community to represent the diversity of the world's talent. We are committed to equality of opportunity, to being fair and inclusive, and to being a place where we all belong.

We therefore particularly encourage applications from candidates who are likely to be underrepresented in UCL's workforce. These include people from Black, Asian and ethnic minority backgrounds; disabled people; LGBTQI+ people; and for our Grade 9 and 10 roles, women.

Our division holds an Athena SWAN Silver award, in recognition of our commitment to advancing gender equality.