Division Chief - Cancer Data and AI
Role details
Job location
Tech stack
Job description
- 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., To request a reasonable accommodation for a disability or if you or someone you know has experienced discrimination or sexual misconduct including sexual harassment, you may contact the Director/Title IX Coordinator in the Office of Equal Opportunity and Affirmative Action (OEO/AA). More information, including the Director/Title IX Coordinator's office address, electronic mail address, and telephone number can be located at: https://www.utah.edu/nondiscrimination/ Online reports may be submitted at oeo.utah.edu jeid-e264b2052a656e4ba5a2d393179b6cd3
Requirements
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Associate or Full Professor with a PhD, MD, or equivalent in computational biology, data science, computer science, engineering, oncology, or related fields.
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Exceptional communication and team-building skills.
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Proven leadership in AI or data science with healthcare research applications.
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Strong publication and funding record. Preferred Expertise:
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Machine learning, generative AI, large language models (LLMs), and data integration.
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Oncology data types: Molecular data (genetics, genomics and epigenomics, spatial -omics, systems biology, molecular epidemiology), EHRs, imaging, digital health, and real-world evidence.
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Bridging research with clinical and population data.
Benefits & conditions
- A collaborative, mission-oriented academic environment. HCI and the University of Utah are known for their highly collaborative and collegial culture, where faculty work across disciplines to solve the most pressing challenges in cancer care. The successful candidate will thrive in this environment, building bridges between clinical, research, and community teams to deliver measurable impact.
- Access to rich datasets and advanced computational infrastructure, with a new $50 million pledge to advance AI for cancer research
- Synergy with Scientific Computing Institute (SCI), the Data Exploration and Learning for Precision Health Intelligence (DELPHI), Responsible Artificial Intelligence (RAI), and other University initiatives
- Strategic partnerships with federal agencies and regional health systems.
- Competitive compensation and benefits.
- Leadership support to establish a nationally recognized center of excellence in cancer data and AI.