Research Scientist - Computational Pathology

Huntsman Cancer Institute; Salt Lake City (UT); On-site; USD 85,000 - 125,000; Full time

Job summary

The Pan Lab at Huntsman Cancer Institute (HCI), University of Utah seeks a highly motivated computational researcher to work on AI and computational approaches for cancer using digital pathology and multi-omics data. You will focus on computational pathology, whole-slide image analysis, and integration with spatial, molecular, and clinical data.

Join a collaborative, interdisciplinary team at HCI and the University of Utah, contributing to translational cancer research with opportunities to work

Qualifications

• PhD or equivalent doctoral degree, or substantial relevant research experience.
• Strong programming skills in Python.
• Experience in Linux/Unix environments and command-line workflows.
• Experience in image processing, computer vision, DL, and/or large language models.
• Familiarity with PyTorch or TensorFlow.
• Ability to develop, debug, and maintain scientific analysis pipelines.
• Strong quantitative problem-solving and independent learning.

Responsibilities

• Develop and maintain computational analysis pipelines for digital pathology and multi-omics data.
• Analyze whole-slide histopathology images and integrate imaging features with spatial, molecular, and clinical data.
• Collaborate across computational, biological, pathological, and clinical teams to translate findings into translational cancer research.

Skills

Python programming

Linux/Unix

Image processing

Computer vision

Deep learning

PyTorch or TensorFlow

Scientific programming

Interdisciplinary collaboration

Education

PhD in Computer Science / Biomedical Engineering / related quantitative field

Tools

PyTorch

TensorFlow

GPU computing

Job description

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.

Learn more about the great benefits of working for University of Utah: benefits.utah.edu

Preferences

Preferred candidates have:

• 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.

Candidates are not expected to have experience in all of these areas. We particularly value strong computational fundamentals, rigorous problem-solving skills, scientific curiosity, and the ability to independently learn new methods.