Assistant to Associate Professor DOQ

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Posting Details

The University of Utah, an AA/EO employer, encourages applications from all qualified individuals, and provides reasonable accommodation to the known disabilities of applicants and employees. The University of Utah values candidates who have experience working in settings with students, staff, faculty and patients from all backgrounds and possess a strong commitment to improving access to higher education, employment opportunities, and quality healthcare for historically underrepresented groups.

Position Information

Position/Rank Assistant to Associate Professor DOQ Department 00222 - Oncological Sciences City Salt Lake City, UT Track Tenure Track New Position to Begin Details

The Department of Oncological Sciences and Huntsman Cancer Institute (HCI) invite applications for tenure-track faculty positions at the assistant or associate professor levels. We seek an outstanding cancer data scientist who will complement existing strengths in the Department in transcriptional regulation, cell signaling, epigenetics, cancer genetics, stem cell biology, genetically-engineered mouse, zebrafish models of cancer, apoptosis, DNA repair, cell motility, cancer metabolism, cancer data science and immuno-oncology.

In addition, HCI has four exceptional Cancer Center Research Programs encompassing the continuum of cancer research from basic, translational, clinical and population sciences. HCI provides an outstanding environment, with state-of-the-art facilities, excellent shared resources, access to clinical samples for research, and NCI Comprehensive Cancer Center designation in a collegial and collaborative Department culture.

This tenure-track position is dedicated to advancing cancer research through expertise in cancer data science, focusing on deep learning, artificial intelligence (AI), generative AI, large language models (LLMs), medical image analysis, digital oncology, and multi-omics data integration. The successful candidate will establish an independent, well-funded research program, contribute to exceptional teaching in our graduate programs, and actively collaborate with bench and clinical researchers across HCI and the broader university.

This position will be hired into the Cluster of Computational Oncology, a highly innovative collaboration between HCI and the Scientific Computing and Imaging (SCI) Institute at the University of Utah. Together we leverage our internationally renowned research strengths to make lifesaving advances in the prevention, detection, diagnosis, and treatment of cancer.

Responsibilities:

* Develop and lead an independent research program focused on applying deep learning and AI to address critical challenges in cancer research, including the leveraging medical image analysis (pathological and/or MRI/CT scan images) and generative AI.

* Secure strong extramural funding and generate high-quality peer-reviewed research articles.

* Contribute to the teaching mission of the department by developing and delivering graduate-level courses in cancer data science and related fields.

* Mentor and guide students and fellows in their research endeavors.

* Actively collaborate with bench and clinical researchers at HCI and across the university to translate research findings into clinical applications and improve patient outcomes

* Participate in departmental and university service activities, and uphold HCI's values.

Qualifications:

* Ph.D. in Computer Science, Data Science, Biomedical Engineering, or related field.

* Demonstrated expertise in deep learning and AI methodologies. Experience in medical image analysis, particularly applied to cancer research (pathology, MRI, CT scans) preferred.

* Ability to secure extramural funding, and a strong publication record in peer-reviewed journals.

* Excellent communication, collaboration, and interpersonal skills.

* Commitment to teaching and mentoring students, and in supporting learners of all backgrounds.

* Alignment with the values of the HCI and the University of Utah.

Applicants for Assistant Professor are expected to hold a PhD or MD/PhD (or equivalent), to have excelled in…