Research Associate in AI for Antifungal Drug Discovery at Imperial College London

Imperial College London is inviting applications for a high-impact post-doctoral Research Associate position within the Ballester group. Funded by the Wellcome Trust, this 24-month project focuses on building an integrated, AI-driven functional genomic and chemoproteomic platform to revolutionize antifungal drug discovery, specifically targeting the critical, multi-drug resistant fungal pathogen Candida auris.

This collaborative project will be carried out in partnership with leading Imperial research groups within the Fleming Initiative, GSK, and the Dundee Drug Discovery Unit, offering an unparalleled opportunity to work at the intersection of artificial intelligence, genomics, and pharmacology.

Key Job Overview

Job Description & Key Responsibilities

Directly managed by Dr. Pedro Ballester, the successful candidate will play a pivotal role in developing state-of-the-art AI frameworks. Key responsibilities include:

• Developing machine learning and AI models to predict whole-cell antifungal activity across ultra-large, synthesis-on-demand chemical libraries.
• Designing AI models to predict antifungal-induced toxicity across various biological systems, including organ-specific iPSC-derived cell lines.
• Utilizing pre- and post-treatment single-cell RNA sequencing (scRNA-seq) profiles of C. auris to construct predictive models determining the susceptibility or resistance of individual isolates based on their baseline transcriptional profiles.
• Supporting the selection of optimal drug therapies and identifying synergistic treatment combinations to combat drug-resistant strains.

Eligibility & Qualifications

The ideal candidate should meet the following criteria:

• Education: Holds (or is about to obtain) a PhD in AI-driven drug discovery, computational biology, bioinformatics, or a closely related quantitative field. (Note: Candidates who have not yet been officially awarded their PhD will be appointed as a Research Assistant).
• Expertise: Demonstrated experience in AI-enabled phenotypic drug discovery, precision oncology, or biomedical bioinformatics.
• Track Record: A strong publication record in reputable peer-reviewed scientific journals.
• Skills: High proficiency in machine learning frameworks, programming (Python/R), and handling complex genomic or chemoproteomic datasets.

What Imperial College London Offers

• Career Growth: Access to Imperial’s sector-leading dedicated career support, training programs, and opportunities for internal promotion.
• Professional Development: 10 dedicated development days per year to build advanced skills and explore future career pathways.
• Supervisory Experience: Opportunities to co-supervise Master’s students and co-author collaborative publications.
• Generous Benefits: An exceptional remuneration package, including 43 days of annual leave (including public holidays and college closures) and highly competitive pension schemes.
• Inclusive Environment: A diverse, collaborative, and highly supportive academic culture.

How to Apply

Interested candidates should submit their application directly to Dr. Pedro Ballester via email. Please ensure your application email contains the following documents as attachments:

1. A comprehensive Curriculum Vitae (CV).
2. A Cover Letter (maximum of two pages) detailing your suitability, research interests, and motivation for the role.
3. A complete List of Publications.

Application Email: p.ballester@imperial.ac.uk

Closing Date for Applications

Wednesday, 28 October 2026

For more details about the group’s research direction, candidates are encouraged to explore the Ballester Group’s publications via the official Imperial College London Job Portal.