The Department of Biomedical Informatics (DBMI) at Harvard Medical School is seeking to fill a tenure-track assistant professor position at the multidisciplinary intersection of artificial intelligence (AI)/machine learning (ML) and clinical decision making. Qualified candidates would be joining a growing department with several leaders in clinical AI, bioinformatics, and population health. DBMI faculty lead or participate in multiple multidisciplinary research and teaching efforts such as the Bioinformatics and Integrative Genomics program, the Division of Health Sciences and Technology of Harvard and MIT, the Data Science Initiative of Harvard University and the Harvard Kempner Institute for the Study of Natural and Artificial Intelligence.

Required Education and Experience

For interdisciplinary AI/ML: Applicants should possess a Ph.D. degree in computer science, biomedical informatics, or comparably quantitative disciplines. Applicants must have demonstrated expertise and impact at the intersection of AI/ML and biomedicine, with ability to make major contributions in both AI/ML methodology and applications in biomedicine.

Preferred Qualifications

Research areas of special interest include:
AI in healthcare; human in the loop or knowledge-enhanced AI; deep learning; natural language processing;  question-answering/conversational AI; brain-inspired computing; semantic/cognitive/perceptual computing; study of health in their natural living environments; AI and Big data – including social, sensor, biological, and health self-reports – and scalable computing/analysis of big and real-world data; AI and computer vision; robotics, cyber-physical systems; embodied AI and embodied systems acting and interacting in the real world human-computer interaction including personal digital/assistive technology.

Application materials should be submitted electronically.

Required Documents

  1. Curriculum Vitae
  2. Cover Letter
  3. Statement of Research
  4. Diversity, Inclusion, and Belonging Statement
  5. Names & contact information of at least 3 references

Review of applications will begin November 30, 2022 and continue until this position is filled. Expected start date is Summer, 2023.

We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, gender identity, sexual orientation, pregnancy and pregnancy-related conditions or any other characteristic protected by law.

If you have any questions, please contact