AI Lead, AIDD

The Artificial Intelligence (AI) in Drug Discovery (AIDD), hosted by the Singapore Agency for Science, Technology and Research (A*STAR), is Singapore's national programme for the utilization of AI in drug discovery. AIDD will develop novel machine learning models and algorithms towards the discovery and validation of drug targets, biomarkers, and molecular entities as therapeutics. A cornerstone of our programme is the AIDD LeadFactory, a central technology platform specifically designed for AI-driven medicinal chemistry. This cutting-edge facility provides the experimental and computational infrastructure to translate AI-generated insights into tangible chemical matter, enabling rapid iteration and validation in the drug discovery pipeline. A key research focus is the discovery, validation, and optimization of small molecules that target proteins and RNA, relevant across various therapeutic areas. We are seeking an AI Lead for the AIDD LeadFactory. As the AI Lead of the AIDD LeadFactory, you will play a pivotal role in driving the success of the AI-driven drug design efforts within the AIDD Programme. You will lead a dynamic group, foster interdisciplinary collaborations, and contribute significantly to our technology development activities, with a strong focus on leveraging and developing the capabilities of the AIDD LeadFactory.Key Responsibilities Strategic leadership : Help develop and execute the scientific vision and strategy for the AIDD LeadFactory's AI-driven drug design, identifying new research avenues and emerging trends to maximize tangible impact. Research excellence : Lead a research group focusing on innovative AI methodologies for drug discovery, including de novo design, virtual screening, binding pose and binding affinity prediction, ADMET prediction, and hit-to-lead optimization, actively integrating experimental validation through the AIDD LeadFactory. Team building and mentorship : Recruit, mentor, and inspire a team of talented researchers (postdocs, PhD students, and scientific staff) in AI and drug discovery, including those focused on the experimental aspects enabled by the LeadFactory. Interdisciplinary collaboration : Strengthen collaborations with experimental and clinical groups both within A*STAR and with external academic and industry partners, leveraging the unique capabilities of the AIDD LeadFactory. Dissemination : Publish high-impact research in top-tier journals and present at international conferences, enhancing the programme"s global visibility and showcasing the innovations stemming from the AIDD LeadFactory. Your Profile We are looking for a highly accomplished and passionate individual with: A PhD in Computational Chemistry, Medicinal Chemistry, Chemoinformatics, Bioinformatics, Computer Science, Machine Learning, or a closely related field. A strong, internationally recognized research track record in AI-driven drug design, evidenced by high-impact publications and distinguished scholarly contributions, including invited talks, conference presentations, and scientific outreach activities Extensive industrial experience leading research teams and managing complex interdisciplinary projects, ideally at the interface of computational and experimental drug discovery. Deep expertise and demonstrated ability to design and develop novel neural network architectures and machine learning methodologies, tailored to address complex problems in molecular design, virtual screening, and predictive modelling. Proven experience or a strong vision for integrating computational design with experimental validation, particularly in the context of automated synthesis and high-throughput screening platforms. Proficiency in computational chemistry software and a deep understanding of medicinal chemistry and drug discovery principles. Excellent communication, interpersonal, and leadership skills, with a proven ability to foster a collaborative and inclusive research environment. A strategic mindset with the vision to drive transformative research at the interface of AI and chemical biology. Prior experience in co-directing or leading a significant research programme or centre is highly advantageous