Associate Professor to Professor DOQ

The Opportunity:

The University of Utah's Department of Oncological Sciences (OncSci), in conjunction with Huntsman Cancer Institute (HCI), invites applications for a visionary and mission-driven leader to serve as a senior faculty member and Chief of the new Division of Cancer Data and Artificial Intelligence (CDAI).

Part of the University of Utah located in Salt Lake City, UT, HCI includes over 300 cancer-focused research teams and has established outstanding programs in laboratory research, clinical cancer research, and cancer control and population sciences and cross-disciplinary disease centers. HCI is the only NCI-designated Comprehensive Cancer Center in the Mountain West, has been rated in the 'exceptional' range at its past two reviews, and serves five states through, research, clinical care, and community outreach and engagement: Utah, Idaho, Montana, Nevada and Wyoming.

Key Responsibilities:

• Define and execute the strategic vision for the CDAI Division, in collaboration with aligned leaders.
• Help recruit faculty to the CDAI Division and, if applicable, to the Vineyard campus.
• Build and manage transdisciplinary teams between the two campuses and across oncological sciences, bioinformatics, and computer science.
• Lead an innovative research program in AI-driven cancer biology, diagnostics, and/or therapeutics.
• Provide mentorship for early career faculty in the CDAI Division and participate in education of the next generation of cancer data scientists by participating in training programs and research mentorship.
• Foster collaborations with academic institutions (e.g., UVU, BYU) and Silicon Slopes tech partners.
• Secure extramural funding and oversee large-scale research initiatives.
• Translate data science innovations into real-world clinical applications.
• Represent the CDAI Division on national and international platforms.

Qualifications:

• Associate or Full Professor with a PhD, MD, or equivalent in computational biology, data science, computer science, engineering, oncology, or related fields.
• Exceptional communication and team-building skills.
• Proven leadership in AI or data science with healthcare research applications.
• Strong publication and funding record.