The Institute for Artificial Intelligence and Data Science at the University at Buffalo, State University of New York, is seeking a highly motivated Research Assistant Professor in Artificial Intelligence (AI) and Health Sciences.
The successful candidate will conduct interdisciplinary research at the intersection of AI, machine learning, and health sciences. The primary research focus will be on developing and applying innovative AI methods to address computational challenges associated with large-scale, high-dimensional biomedical data, including medical imaging, genomics, and clinical data. The candidate will work closely with investigators across AI, biomedical research, and health sciences to develop computational approaches that address important biomedical and clinical problems. In addition to conducting original research, the successful candidate will perform comprehensive and systematic literature reviews of emerging developments at the intersection of AI and health sciences. The candidate will synthesize advances across multiple health science domains, identify major research trends, unmet needs, methodological gaps, and opportunities where AI could have significant impact, and use these insights to help develop new interdisciplinary research directions and collaborations. The ideal candidate will have interdisciplinary training and demonstrated experience bridging methodological AI research and biomedical or health science applications.
Qualifications:
Ph.D. in bioinformatics, computational biology, computer science, electrical or computer engineering, mathematics, statistics, biomedical informatics, or a closely related field.
Strong background in AI, machine learning, statistics, and computational sciences.
At least three years of research experience developing and/or applying AI and machine learning methods to biomedical or health science applications.
Proficiency in Python, R, MATLAB, or other relevant programming languages and computational tools.
Demonstrated research productivity, preferably evidenced by peer-reviewed publications in AI, machine learning, bioinformatics, biomedical informatics, or related areas.
Strong written and oral communication skills.
Ability to work effectively both independently and as part of interdisciplinary research teams.
