Research Fellow in Bioinformatics

UCL Computer Science, Faculty of Engineering

Job Description

Research Fellow in Bioinformatics

Department: Computer Science

Grade: 7

Location: London

Reports to

Professor of Bioinformatics (Prof. David T. Jones)

Context

This Wellcome-funded project, LIGMAP, is developing AI-based methods for characterising and predicting protein pockets and their natural-ligand interactions across the human proteome. LIGMAP is a five-work-package collaboration between UCL (Prof. David Jones, Prof. Christine Orengo and Dr Brooks Paige) and EMBL-EBI (Dr Sameer Velankar and Dr Noel O'Boyle). This post is based in Work Package 2, led by Prof. Jones and funded for up to 4.5 years. WP2 provides the structural models and knowledge-graph infrastructure on which pocket detection, pocket characterisation and ligand prediction across the consortium depend.

WP2 will generate comprehensive, high-fidelity, all-atom structural models of human proteins and their native assemblies, including all polypeptide chains, post-translational modifications and relevant small-molecule cofactors or ligands such as heme, metal ions and FAD. Work will begin with the Structural Genomics Consortium's Target 2035 set of structurally and functionally uncharacterised but disease-relevant human proteins, representing roughly 10% of the human proteome, before extending to the complete human proteome and then to viral and neglected tropical disease pathogen proteomes. The Jones lab has a long-established record in protein structure prediction, machine-learning-based annotation and web-service delivery, supported by dedicated

GPU and high-performance storage resources. Its work on multimodal protein language models and The Encyclopedia of Domains, developed with the Orengo lab, provides a strong technical foundation for delivering an openly accessible, uncertainty-aware structural resource with the UCL and EMBL-EBI partners.

Main purpose of the job

The Research Fellow will develop and benchmark bioinformatics methods, software and empirical workflows for WP2. The role will curate sequence, domain, interaction and ligand data from UniProtKB/Swiss-Prot, IntAct, STRING, the PDB and TED; develop literature-mining and sequencebased pipelines; and integrate the results into a knowledge graph linking residues, ligands and interfaces to experimental evidence and confidence scores. A fine-tuned LLM agent will monitor the PDB, UniProt, ChEMBL and PubMed, extract interaction data with structure-aware predictors, resolve entities and synonyms, update interaction types, affinities and confidence attributes, and flag

inconsistent or outdated links. Initially, this system will support human curation of reproducible model-definition JSON files, progressing towards greater automation as coverage expands.

The role will also implement a tiered modelling strategy using AlphaFold3 with explicit ligand templates for monomers and homo-oligomers, Boltz-2 for flexible regions, and AlphaFold-Multimer and Boltz-2 for heteromeric assemblies. Predictions will be supported by interaction data and crossvalidated against cross-linking, cryo-EM or mutagenesis data where available. Targets will also be modelled with open-licence predictors, including Boltz-2, OpenFold3, RoseTTAFold-All-Atom, OmegaFold and ESMFold. Models will be benchmarked against newly released PDB structures using measures such as DockQ and MolProbity, assessed with the group's quality-assessment stack, and represented by multiple conformers where needed. The postholder will help develop deep atomic pocket embeddings ("pocketprints") and support staged public releases through 3D-Beacons for integration with PDBe-KB, UniProt and InterPro.

Duties and responsibilities

• Develop and benchmark new bioinformatics and machine-learning methods that address the project's research goals.
• Develop, test, document and maintain research software according to best practice in scientific computing.
• Support the development and maintenance of the group's web services, software resources and relevant web pages.
• Contribute to the design of experiments and empirical studies in consultation with the Principal Investigator.
• Set up and run data collection, experiments, program building and related empirical activities with appropriate supervision and support.
• Record, analyse and write up experimental results promptly, ensuring that methods, results and generated data are properly archived.
• Lead the planning and documentation of the project and contribute to effective delivery across the collaboration.
• Prepare and present research findings to colleagues for review and incorporate feedback into subsequent work.
• Represent the project at relevant workshops and conferences.
• Contribute to papers for submission to appropriate peer-reviewed journals and conferences.
• Prepare progress reports for funding bodies and the advisory board as required.
• Contribute to the preparation and drafting of research bids and proposals.
• Undertake background literature reviews and prepare posters, presentations and relevant training materials.
• Contribute to the activities of the research team and department, including supervising project students if requested.
• Record skills training and continuing professional development activities periodically using UCL's web-based system.

General

• Follow and actively promote the UCL Ways of Working.
• Takes responsibility to carry out duties in a way that embodies UCL's environmental and social sustainability values, actively supporting UCL's Sustainability Strategy, policies and objectives within the remit of their role.

• Follow UCL policies, including Equal Opportunities and Equality policies, and observe Fire and Health and Safety Regulations.
• Ensure that equipment is safe and maintained in working order and that work complies with departmental security policy.
• Carry out any other duties within the scope, spirit and purpose of the job as requested by the line manager.
• This job description may be reviewed and be subject to amendment in consultation with the post holder.

Person Specification

Note to job applicant: Copy and paste the following criteria into your Statement in support of your application and describe under each criterion how you meet it, giving examples. You will be scored on how you meet each criterion.

Essential Criteria

Qualifications, experience and knowledge

A PhD in Bioinformatics, Computational Biology or Computer Science, or a PhD in a related discipline where the thesis involved bioinformatics research. Candidates without a PhD may be considered only in exceptional cases where they have an extensive, proven track record of relevant bioinformatics work.

Knowledge of research techniques and methodologies relating to protein sequences and/or structures.

Experience of working in a research environment.

Experience of developing and testing algorithms for bioinformatics applications.

Experience of machine-learning algorithms.

Skills and abilities

Strong Linux software-development skills and a good working knowledge of scientific-computing best practice, including documentation and version control.

Expertise in several programming languages, including Python.

Strong scientific research skills spanning theoretical and empirical work, planning and documentation.

Ability to analyse data and communicate the results clearly in writing.

Effective written and verbal communication skills.

Ability to organise work effectively and meet deadlines while maintaining accuracy and attention to detail.

UCL Ways of Working

Ability to work effectively and collaboratively as part of a team.

Desirable Criteria Application form/Interview Application form/Interview Application form/Interview Application form/Interview Application form/Interview Application form/Interview Application form/Interview Application form/Interview Application Experience of AI or deep-learning methods in structural bioinformatics.

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Experience of developing or maintaining bioinformatics web servers.

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