Research Scientist - Computational Pathology and AI in Cancer Research

Utah; Salt Lake City (UT); On-site; USD 36,000 - 83,000; Full time

Job summary

The Pan Lab at the Huntsman Cancer Institute (HCI), University of Utah is seeking a highly motivated computational researcher to join our interdisciplinary research team.

Our lab develops artificial intelligence (AI) and computational approaches to study cancer using digital pathology and multi-omics data, with an emphasis on translating quantitative tissue phenotypes into biologically and clinically meaningful insights.

Qualifications

• A Ph.D. or equivalent doctoral degree, or substantial relevant research experience, in Computer Science, Biomedical Engineering, Electrical/Computer Engineering, Bioinformatics, Computational Biology, Data Science, Applied Mathematics, Statistics, or a related quantitative discipline.
• Strong programming skills in Python.
• Experience working in a Linux/Unix environment, including command-line workflows.
• Experience in image processing, computer vision, deep learning, and/or large language models.
• Familiarity with modern deep-learning frameworks such as PyTorch or TensorFlow.
• Ability to independently develop, debug, and maintain scientific analysis pipelines.
• Strong quantitative problem-solving skills and the ability to learn new computational methods independently.
• Effective communication skills and the ability to work collaboratively in an interdisciplinary research environment.
• Desirable: Computational pathology; multimodal ML; spatial omics; GPU computing; reproducible environments.

Responsibilities

• Development and application of computer vision and deep learning methods for pathology images, including tissue and cellular segmentation, classification, and quantitative image analysis.
• Development and maintenance of scalable and reproducible computational pipelines for large pathology and multi-omics datasets.
• Characterization of tumor morphology, tissue architecture, immune and stromal microenvironments, and spatial heterogeneity.
• Integration of digital pathology with spatial transcriptomics, spatial proteomics, and other molecular data.
• Development of multimodal approaches for biomarker discovery, patient stratification, and outcome prediction.
• Analysis of large datasets using Linux-based high-performance and GPU computing environments.
• Collaboration with bioinformatician, pathologists, cancer biologists, and clinical investigators to design analyses and interpret results.
• Preparation of scientific manuscripts and presentation of research findings at internal meetings and national/international conferences.

Skills

Python

Linux/Unix

Computer Vision

Deep Learning

Scientific Programming

Education

PhD in a scientific discipline

Tools

PyTorch

TensorFlow

Job description

Job Summary

The Pan Lab at the Huntsman Cancer Institute (HCI), University of Utah is seeking a highly motivated computational researcher to join our interdisciplinary research team. Our lab develops artificial intelligence (AI) and computational approaches to study cancer using digital pathology and multi-omics data, with an emphasis on translating quantitative tissue phenotypes into biologically and clinically meaningful insights. We are particularly interested in candidates with strong computational skills in computer vision, deep learning, image processing, and scientific programming. The successful candidate will work primarily on computational pathology and multimodal cancer research, including analysis of whole-slide histopathology images and integration of imaging-derived features with spatial, molecular and clinical data. The Pan Lab is based at Huntsman Cancer Institute and the Department of Oncological Sciences at the University of Utah. Our research lies at the intersection of artificial intelligence, computational pathology, spatial biology, and precision oncology. The successful candidate will have opportunities to work with large-scale digital pathology and molecular datasets, develop new computational methodology, collaborate across computational, biological, pathological, and clinical disciplines, and contribute to high-impact translational cancer research. Huntsman Cancer Institute is committed to cancer prevention, care, and survivorship for all communities within the area we serve – which includes Idaho, Montana, Nevada, Utah, and Wyoming – with impact worldwide. In your cover letter or during your interview process, we invite you to share how your professional experiences have prepared you to serve as a member of our team as we work to reduce the cancer burden experienced by all people and communities. This may include description of your prior experiences related to research, prevention, clinical care, community engagement/outreach, training, administration, or other areas relevant to Huntsman Cancer Institute's mission and this position.

Research Areas and Responsibilities

• Development and application of computer vision and deep learning methods for pathology images, including tissue and cellular segmentation, classification, and quantitative image analysis.
• Development and maintenance of scalable and reproducible computational pipelines for large pathology and multi-omics datasets.
• Characterization of tumor morphology, tissue architecture, immune and stromal microenvironments, and spatial heterogeneity.
• Integration of digital pathology with spatial transcriptomics, spatial proteomics, and other molecular data.
• Development of multimodal approaches for biomarker discovery, patient stratification, and outcome prediction.
• Analysis of large datasets using Linux-based high-performance and GPU computing environments.
• Collaboration with bioinformatician, pathologists, cancer biologists, and clinical investigators to design analyses and interpret results.
• Preparation of scientific manuscripts and presentation of research findings at internal meetings and national/international conferences.

Minimum Qualifications

EQUIVALENCY STATEMENT: 1 year of higher education can be substituted for 1 year of directly related work experience (Example: bachelor's degree = 4 years of directly related work experience). Department may hire employee at one of the following job levels: Research Scientist, I: Requires a PhD in a scientific discipline, or an equivalent combination of education and directly related experience.

Preferences

• A Ph.D. or equivalent doctoral degree, or substantial relevant research experience, in Computer Science, Biomedical Engineering, Electrical/Computer Engineering, Bioinformatics, Computational Biology, Data Science, Applied Mathematics, Statistics, or a related quantitative discipline.
• Strong programming skills in Python.
• Experience working in a Linux/Unix environment, including command-line workflows.
• Experience in image processing, computer vision, deep learning, and/or large language models.
• Familiarity with modern deep-learning frameworks such as PyTorch or TensorFlow.
• Ability to independently develop, debug, and maintain scientific analysis pipelines.
• Strong quantitative problem-solving skills and the ability to learn new computational methods independently.
• Effective communication skills and the ability to work collaboratively in an interdisciplinary research environment.
• Experience in one or more of the following areas is desirable: Computational pathology; Deep learning for image segmentation, classification, object detection, representation learning, or related computer-vision tasks; Spatial transcriptomics or spatial proteomics, including platforms such as 10x Visium or Xenium; Multimodal machine learning and image-omics integration; High-performance/GPU computing, workload schedulers, containers, and reproducible computational environments; Scientific productivity demonstrated through peer-reviewed publications, conference presentations, software, or other research outputs.

Special Instructions

• Requisition Number: PRN46548B
• Full Time | Part Time? Full Time
• Work Schedule Summary: Department: 02322 - HCI Onc Sci Research Support
• Location: Campus
• Pay Rate Range: $36,196 to $83,036
• Close Date: 12/31/2026