Assistant​/Associate Professor in Computer Science and Artificial Intelligence

Job Title

Assistant/Associate Professor in Computer Science and Artificial Intelligence

We are seeking an accomplished scholar and thought leader in computer science and artificial intelligence to join our faculty at the rank of Assistant or Associate Professor, commensurate with experience. The successful candidate will be based at the University of Maryland Institute for Health Computing (UM-IHC), a major computational research hub in North Bethesda that applies next-generation computational analytics and artificial intelligence to improve health and human disease.

The UM-IHC is equipped with a high-performance computing cluster and access to multiple real-world clinical data sets. While the position sits within a health and biomedical research environment, its scope extends broadly across computer science and AI — including machine learning, deep learning, natural language processing, and emerging foundation model architectures — with the expectation that the successful candidate will help set research direction and computational strategy for the Institute, not simply apply existing methods to clinical problems.

The ideal candidate will bring an independent, extramurally funded research program, a strong publication record, and a vision for how advances in computer science and AI can transform biomedical and clinical research.

• Provide strategic and technical thought leadership on computational methods and AI strategy for the Institute for Health Computing.
• Integrate advanced mathematical and computational modeling to predict health outcomes such as treatment response, hospitalizations, and other clinically meaningful endpoints.
• Establish and lead an independent, extramurally funded research program in computer science and artificial intelligence, with applications spanning clinical, biological, environmental, and other complex health-related data domains.
• Secure and sustain extramural research funding.
• Design and oversee data analysis and computational pipelines, including data extraction, cleaning, transformation, quality assurance, and pipeline monitoring and maintenance.
• Develop novel machine learning, deep learning, and artificial intelligence methodologies — including next-generation approaches such as foundation models and large language models — and apply them to health and biomedical big data.
• Publish high-impact, peer-reviewed research in leading computer science, artificial intelligence, biomedical informatics, and clinical journals.
• Design and conduct research studies in collaboration with other faculty, students, postdoctoral fellows, and research staff.
• Collaborate with clinicians, scientists, and cross-disciplinary teams to translate computational and AI research findings into clinical and biomedical practice.
• Promote responsible, equitable AI by developing methods that identify and mitigate bias and advance health equity.
• Mentor graduate students, postdoctoral fellows, and junior researchers, and represent the Institute in the broader computer science/AI research community (e.g., conference leadership, editorial boards, advisory panels).

• Strong programming skills (e.g., Python, R, or comparable languages) and experience building and deploying computational pipelines at scale.
• Demonstrated expertise in machine learning and/or artificial intelligence, with strong foundations in computer science (algorithms, systems, or theory) alongside applied statistical methods.
• Experience applying AI/ML methods to clinical, biomedical, or health-related data.
• Experience with clinical data and clinical research methods.
• A record of independent, peer-reviewed scholarship and grant-seeking appropriate to the rank of Assistant or Associate Professor.
• Excellent analytical and problem-solving skills, with the ability to lead as well as collaborate across disciplinary teams.
• Excellent written and oral communication and interpersonal skills.
• Experience mentoring or supervising students, postdoctoral fellows, or research staff.

• Expertise in deep learning frameworks (e.g., PyTorch, Tensor Flow) and modern architectures such as…