Program Director

The role of the AIDD Program Director The Singapore national program for the utilization of AI in Drug Discovery (AIDD), funded by the Singapore National Research Foundation (NRF) and hosted by the Singapore Agency for Science, Technology and Research (A*STAR), seeks a Program Director to lead the multi-year initiative and deliver on its vision. AIDD is focused on developing innovative tools and technologies to accelerate drug discovery, with a particular emphasis on unlocking new druggable spaces such as RNA-targeting molecules for example. Through the use of AI-driven strategies, AIDD aims to accelerate target identification to lead discovery while also advancing novel small molecules and other therapeutic modalities for next generation drug development. AIDD will also deepen and expand industry collaborations, partnering with biopharma companies and other stakeholders such as EDDC towards achieving translational impact and proof of value. The Program Director is responsible for: Providing strategic leadership in AI-driven drug discovery, guiding the programme from early-stage conceptualization to the successful validation and optimization of novel drug candidates. Leveraging hybrid domain expertise in drug development and machine learning/artificial intelligence (ML/AI) to accelerate drug discovery efforts. Demonstrating deep understanding of RNA biology, including RNA structure, function, and mechanisms, with a clear drive to apply this knowledge to drug discovery, particularly RNA-targeted therapies to build on Singapore’s emerging RNA efforts. Resource allocation and management: Planning and overseeing the allocation of financial, human (e.g., scientists, engineers, project managers), and technological resources (e.g., computing infrastructure, software licenses, laboratory infrastructure) to ensure efficient and effective execution of research and development activities. Process design and optimization: Establishing and refining workflows, protocols, and best practices for all operational aspects of the AIDD Program, from data acquisition and model development to experimental validation and compound synthesis. This includes identifying bottlenecks and implementing solutions to improve efficiency. Technology and platform strategy: Determining which AI/ML models, computational platforms, and experimental technologies will be utilized and integrated into the program’s operations to maximize its capabilities. Risk management: Identifying potential operational risks (e.g., technical challenges, resource constraints, intellectual property concerns) and developing mitigation strategies. Performance monitoring and evaluation: Track the program’s progress, assess the effectiveness of its operations, and ensure alignment with strategic goals. This includes defining metrics for project success, efficiency, and impact. Cross-functional coordination: Foster seamless collaboration and communication among internal AIDD teams and with external industry partners. Timeline and deliverable management: Setting realistic timelines for program milestones and ensuring that deliverables are met on schedule and within budget. Stakeholder communication: Regularly communicating program status, progress, and challenges to key stakeholders, including leadership, funding bodies, and collaborators. Ensuring compliance: Adhering to relevant regulatory, ethical, and internal policies related to data handling, research conduct, and drug discovery and development. Requirements The AIDD Program Director should embody a hybrid leadership profile: combining deep scientific expertise with strong operational acumen, adept at effectively leading and managing diverse teams to leverage cutting-edge AI for drug discovery, and fulfilling the following requirements: Ph.D. or equivalent degree in the life sciences/pharmaceutical sciences and/or computer/data sciences At least 10 - 15 years of experience in the biotechnology, pharmaceutical, or healthcare AI sector, with a strong track record in drug discovery and development. Demonstrated leadership in AI-driven drug discovery programmes across multiple therapeutic areas and modalities, including RNA-based approaches. Hybrid domain expertise in drug development, computer science and machine learning/artificial intelligence (ML/AI) Proven ability to efficiently use cloud computing infrastructure Deep understanding of RNA biology, including RNA structure, function, and mechanisms, with a clear drive to apply this knowledge to drug discovery, particularly RNA-targeted therapies. Proven experience in pharmaceutical business development, including partnerships and translational collaborations. A strong grasp of the underlying biology, chemistry, and pharmacology relevant to drug discovery. Extensive industry experience in biotechnology or pharmaceuticals, with a demonstrated track record of impact in AI-driven drug discovery and development across various therapeutic areas and modalities, including RNA-based approaches. Strong communication, collaboration, and leadership skills to effectively engage with stakeholders across academia, industry, and government. Global experience or demonstrated ability to work with international teams across time zones and cultures. #J-18808-Ljbffr