Postdoc: AI-Driven Antifungal Drug Discovery

SFBI; Greater London; On-site; GBP 38,000 - 52,000; Full time

Benefits offered by this job

Co-supervise master students

Career support for researchers

Development days

Job summary

Imperial College London is seeking a post-doctoral Research Associate to build an AI-driven platform for antifungal drug discovery, focusing on C. auris.

You will work within the Ballester group on integrating genomic and chemoproteomic data, funded by the Wellcome Trust, in collaboration with other Imperial groups, GSK and the Dundee Drug Discovery Unit. The role involves developing AI models for antifungal activity and toxicity, leveraging scRNA-seq data, and contributing to high-impact

Qualifications

• PhD in AI-driven drug discovery with published work.
• Experience in AI-enabled phenotypic drug discovery.
• Strong publication record in relevant fields.

Responsibilities

• Develop AI models predicting whole-cell antifungal activity on ultra-large chemical spaces.
• Model antifungal-induced toxicity across biological contexts including iPSC-derived lines.
• Utilise pre-treatment scRNA-seq profiles to predict susceptibility of C. auris isolates.

Skills

PhD in AI-driven drug discovery

AI-enabled phenotypic drug discovery

Strong publication record

Postdoc research experience

Education

PhD in AI-driven drug discovery

Tools

Python

TensorFlow/PyTorch

Job description

Imperial College London is seeking a post-doctoral Research Associate to build an AI-driven platform for antifungal drug discovery, focusing on C. auris.

You will work within the Ballester group on integrating genomic and chemoproteomic data, funded by the Wellcome Trust, in collaboration with other Imperial groups, GSK and the Dundee Drug Discovery Unit. The role involves developing AI models for antifungal activity and toxicity, leveraging scRNA-seq data, and contributing to high-impact