Assistant Professor, AI Pathogen Genomics

NUS Centre for Cancer Research (N2CR) | NUS Medicine; Murphy (NC); On-site; USD 117,000 - 164,000; Full time

Job summary

Duke-NUS Medical School invites applications for an Assistant Professor, AI Pathogen Genomics. This joint appointment with the Duke-NUS COP and CBDS will advance research and platform development at the interface of AI and pathogen genomics, with regional health security impact.

The candidate will lead applied research, design AI-enabled genomics methods, build collaborations across academic and public health partners, contribute to grants, and mentor students and staff in a dynamic,

Qualifications

• PhD or equivalent in AI/ML, computational biology, bioinformatics, genomics, infectious disease modelling, biomedical data science, statistics, computer science or closely related field.
• Senior/leadership experience with research independence and ability to lead teams (e.g., postdoctoral or equivalent) as required for senior appointments.
• Proven expertise in AI/data science methods applied to genomics, omics, infectious diseases or public health surveillance.

Responsibilities

• Lead applied research at the interface of AI, pathogen genomics and outbreak preparedness.
• Design, develop and evaluate AI-enabled methods for pathogen genomic analysis and surveillance.
• Build collaborations with Duke-NUS, SingHealth, public health agencies and international partners.
• Contribute to grant proposals, research strategy, donor engagement and externally funded programmes.

Skills

AI/ML in Genomics

Collaborative leadership

Grant writing

Education

PhD or equivalent doctoral qualification in AI/ML/Computational biology/biomedical data science

Job description

Assistant Professor, AI Pathogen Genomics

Job Title: Assistant Professor, AI Pathogen Genomics

University-Level Unit: Duke-NUS Medical School

Faculty/Department-Level Unit: Dean's Office

Employee Category: Research Staff

Location: Outram Campus

Job Description

The Duke-NUS Centre for Outbreak Preparedness (COP) works to strengthen communicable disease preparedness and response capacity across South and Southeast Asia. COP also hosts the Asia Pathogen Genomics Initiative (Asia PGI), a regional network supporting 15 countries to strengthen pathogen genomics surveillance, data use and translation for public health action. The Duke-NUS Centre for Biomedical Data Science (CBDS) provides a strategic hub for data science, artificial intelligence, statistical methodology, computational omics and systems biology, supporting biomedical discovery and translational impact across Duke-NUS, SingHealth, the Academic Medical Centre and wider regional and global partners. This joint appointment will advance research and platform development at the interface of AI and pathogen genomics, bringing together COP’s applied focus on infectious disease threats and regional preparedness with CBDS’s depth in biomedical data science, AI and computational biology.

Key Responsibilities Will Include:

• Lead and develop applied research at the interface of AI, pathogen genomics and outbreak preparedness, in close collaboration with COP and CBDS faculty and partners.
• Design, develop and evaluate AI-enabled methods for pathogen genomic analysis, including approaches for variant detection, lineage classification, antimicrobial resistance prediction, outbreak clustering, genomic representation learning, multi-modal data integration and decision support.
• Build collaborations across Duke-NUS, SingHealth, national public health agencies, regional academic partners, ministries of health, international organisations and technology partners.
• Contribute to grant proposals, research strategy, donor engagement and externally funded programmes in AI, pathogen genomics, infectious disease surveillance and regional health security.
• Publish high-quality scientific papers, technical reports, policy briefs and other outputs that advance the field and support translation into public health practice.
• Support robust, reproducible and ethically governed analytical workflows, including attention to data quality, privacy, security, sovereignty, transparency, validation and responsible AI.
• Provide scientific and technical leadership to research staff, data scientists, students and collaborators, including supervision, mentorship and capacity development.
• Contribute to education and training in AI, computational genomics, biomedical data science and outbreak analytics for Duke-NUS learners and regional partners.
• Help translate analytical outputs into practical insights for surveillance, preparedness, outbreak response and policy decision-making.
• Perform other related duties as required by COP and CBDS leadership.

Qualifications

• PhD or equivalent doctoral qualification in artificial intelligence, machine learning, computational biology, bioinformatics, genomics, infectious disease modelling, biomedical data science, statistics, computer science or a closely related field.
• Minimum experience commensurate with appointment: Senior Research Fellow - normally at least 5 years of postdoctoral or equivalent research experience; Principal Research Scientist - normally at least 6 years of relevant experience with evidence of research independence and leadership; Assistant Professor (Practice Track) - substantial applied research/practice experience with evidence of teaching, mentorship or capacity development.
• Demonstrated expertise in AI/data science methods applied to genomics, omics, infectious diseases, public health surveillance or related biomedical domains.
• Strong technical skills in areas such as machine learning, statistical learning, scalable analytical pipelines, software engineering, cloud or high-performance computing, federated or privacy-preserving analytics, knowledge graphs, LLMs or multi-modal data integration.
• Track record of high-quality research outputs, technical delivery, grant/proposal development, team science and effective communication with academic, public health and technical stakeholders.

Ideal Candidate

The ideal candidate will combine scientific credibility with practical implementation experience. They should be comfortable working across disciplines, from machine learning and genomics to public health and policy, and motivated to build AI-enabled genomic intelligence approaches that are rigorous, responsible and useful for real-world outbreak preparedness in Asia and beyond.