Research Associate: AI-Driven Antifungal Target Discovery

Imperial Enterprise; Greater London; Hybrid; GBP 45,000 - 49,000; Full time

Benefits offered by this job

Career development and training

Collaborations and networking

Flexible working policy

Cycle-to-work scheme

Season ticket loan

Job summary

Imperial College London is seeking a Research Associate to join an AI-driven antifungal drug discovery program targeting Candida auris. You will work at the interface of fungal genetics, chemical biology and machine learning, contributing to discovery of novel targets with minimal human toxicity risk.

You will lead chemoproteomic profiling, develop CRISPR-based annotations, and perform high-throughput screens while collaborating across disciplines and institutions.

Qualifications

• Practical experience in fungal or yeast molecular biology and genetic manipulation.
• Experience with CRISPR/Cas9 genome editing techniques.
• Understanding of fungal biology and/or medical mycology.
• Experience of international, multidisciplinary collaboration.

Responsibilities

• Lead chemoproteomic profiling of Candida auris to identify druggable sites.
• Develop and apply CORe CRISPR-based annotation of targets.
• Design and deliver high-throughput CRISPR knockout screens to define gene essentiality.
• Collaborate with computational colleagues to integrate multi-omics data for target prioritisation.
• Contribute to evolutionary and toxicity profiling of prioritised targets.
• Work with Imperial, University of Dundee, GSK and Cultivarium teams.
• Prepare manuscripts, present findings at conferences, and assist grant proposals.
• Supervise the project’s Research Assistant and students.

Skills

Fungal biology

CRISPR/Cas9

Genetic manipulation

International collaboration

Education

PhD in molecular microbiology or related field

Job description

Imperial College London is seeking a Research Associate to join an AI-driven antifungal drug discovery program targeting Candida auris. You will work at the interface of fungal genetics, chemical biology and machine learning, contributing to discovery of novel targets with minimal human toxicity risk.

You will lead chemoproteomic profiling, develop CRISPR-based annotations, and perform high-throughput screens while collaborating across disciplines and institutions.