Assistant to Associate Professor DOQ

University of Utah; Salt Lake City (UT); On-site; USD 80,000 - 100,000; Full time

Job summary

An established industry player in higher education is seeking a dynamic cancer data scientist for a tenure-track faculty position. This role focuses on advancing cancer research through innovative applications of deep learning and AI. The successful candidate will establish a well-funded research program, contribute to exceptional graduate teaching, and collaborate across disciplines to enhance patient outcomes. With access to state-of-the-art facilities and a commitment to diversity, this opportunity promises a rewarding career in a supportive and collaborative environment. If you are passionate about making a significant impact in cancer research and education, this position is for you.

Qualifications

• Ph.D. in relevant fields with expertise in deep learning and AI methodologies.
• Strong publication record and ability to secure funding.

Responsibilities

• Develop and lead an independent research program in cancer data science.
• Contribute to teaching and mentor students in graduate programs.

Skills

Deep Learning

Artificial Intelligence (AI)

Medical Image Analysis

Multi-Omics Data Integration

Collaboration

Communication

Education

Ph.D. in Computer Science

Ph.D. in Data Science

Ph.D. in Biomedical Engineering

Job description

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 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: 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. 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.

Responsibilities:

1. Develop and lead an independent research program focused on applying deep learning and AI to address critical challenges in cancer research.
2. Secure strong extramural funding and generate high-quality peer-reviewed research articles.
3. Contribute to the teaching mission of the department by developing and delivering graduate-level courses in cancer data science and related fields.
4. Mentor and guide students and fellows in their research endeavors.
5. Actively collaborate with bench and clinical researchers at HCI and across the university to translate research findings into clinical applications and improve patient outcomes.
6. Participate in departmental and university service activities, and uphold HCI’s values.

Qualifications:

1. Ph.D. in Computer Science, Data Science, Biomedical Engineering, or related field.
2. Demonstrated expertise in deep learning and AI methodologies. Experience in medical image analysis, particularly applied to cancer research (pathology, MRI, CT scans) preferred.
3. Ability to secure extramural funding, and a strong publication record in peer-reviewed journals.
4. Excellent communication, collaboration, and interpersonal skills.
5. Commitment to teaching and mentoring students, and in supporting learners of all backgrounds.
6. Alignment with the values of 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 their postdoctoral training and to have a track record of impact and research productivity. Applicants for senior positions should additionally have a proven record of independent funding, leadership, and innovative research.

For additional questions, please contact the Search Committee Chair, Dr. Aik Choon Tan [e-mail]. Candidates should submit a curriculum vitae, a cover letter containing a description of professional experience (including scientific accomplishments, leadership responsibilities, and 3 references), and a 3-page research plan. We encourage applications from candidates of all backgrounds.

Candidates are encouraged to apply by December 31, 2024 at the following link: https://utah.peopleadmin.com/postings/172824

EEO/Non-Discrimination Information:

All qualified individuals are strongly encouraged to apply. Veterans’ preference is extended to qualified applicants, upon request and consistent with University policy and Utah state law. Upon request, reasonable accommodations in the application process will be provided to individuals with disabilities.

The University of Utah is an Affirmative Action/Equal Opportunity employer and does not discriminate based upon race, ethnicity, color, religion, national origin, age, disability, sex, sexual orientation, gender, gender identity, gender expression, pregnancy, pregnancy-related conditions, genetic information, or protected veteran’s status.

This position may require the successful completion of a criminal background check and/or drug screen and immunizations.

Special Instructions for Candidates:

Open Date: Open Until Filled: Yes

Requisition Number: PRN03682F

Type: Faculty

Posting Specific Questions

Required fields are indicated with an asterisk (*).

Required Documents:

• Cover Letter
• Curriculum Vitae
• Research Statement

Optional Documents:

• Appropriate discharge document (such as a DD-214 – Member Copy 4) – Veteran Only
• Letter of Recommendation 1
• Letter of Recommendation 2
• Letter of Recommendation 3
• List of References