• Research and development:
  • Conduct research to design, implement, and refine deep learning algorithms, particularly focusing on analysis tasks relevant to medical imaging, including semantic segmentation and classification.
• Data handling:
  • Work with large-scale medical imaging datasets, developing pre-processing and data curation pipelines, managing data storage, and ensuring data quality.
• Scalability:
  • Develop scalable deep learning solutions capable of handling large-scale, gigantic imaging data during training, as well as providing scalable and real-time inference.
• Explainability and interoperability:
  • Design and implement methods to make deep learning models more interpretable and explainable to clinicians and other stakeholders.
• Benchmarking and evaluation:
  • Set up robust benchmarking tests for comparing models, analyzing metrics such as accuracy, computational efficiency, memory footprint, and scalability.
• Collaboration:
  • Work closely with a multidisciplinary team of engineers, clinicians, and domain experts to ensure models are tailored to medical needs, balancing precision and operational efficiency.
• Reporting:
  • Document and present research findings to stakeholders, preparing comprehensive reports, papers, and presentations to showcase project progress and achievements.

• Educational background:
  • M.Sc. in Computer Science, Data Science, or a closely related field awarded at time of the hire date.
• Deep Learning expertise:
  • Minimum 2 years of hands-on experience designing, developing, training, and evaluating deep learning solutions, with a focus on state-of-the-art convolutional and transformer-based network architectures.
• Medical imaging knowledge:
  • Familiarity with handling medical imaging datasets and understanding their unique challenges.
• High performance computing:
  • Experience in developing scalable deep learning solutions that can handle large-scale imaging data, as well as scalable and real-time inference.
• Explainable AI:
  • Understanding of techniques and methodologies for making deep learning solutions more interpretable and explainable.
• Programming skills:
  • Strong programming skills in both C++ and Python, with hands-on experience using machine learning frameworks like TensorFlow and PyTorch.
• Software development proficiency:
  • Capable of writing well-documented, maintainable code, and implementing unit tests to ensure functionality and reliability. Competence in git and GitHub is a must. Debugging and critical thinking skills including identifying bottlenecks, and bugs and devise solutions to these problems.

• Research & analytical skills:
  • Demonstrated experience in conducting scientific research, interpreting results, and making data-driven decisions. Individuals having a proven track record of research in two or more of the following areas are highly preferred: image analysis, computer vision, probabilistic modeling, uncertainty quantification, scientific visualization, and/or applied mathematics. Analytical problem-solving and decision-making skills needed to independently propose solutions for identified problems.
• Domain-specific knowledge:
  • Prior hands-on experience working on projects related to medical imaging with multiple modalities such as CTs, MRIs, and histopathology images.
• Distributed computing:
  • Familiarity with distributed training methodologies, including data and model parallelism. Proficiency in GPU programming and kernel-based programming for deep learning, including the ability to optimize deep learning algorithms at a low level, is a plus.
• Multi-resolution & compression techniques:
  • Understanding of techniques that balance high-resolution processing with computational efficiency, such as data compression and multi-scale modeling.
• Other technical skills:
  • Experience with large software development projects is a plus. Good understanding of GitHub Actions, or a willingness to learn. Experience with Google Test (for developing unit tests), or a willingness to learn.

• Able to work independently and professionally with minimal supervision and direction.
• Being self-motivated and having good organizational, communication, and teamwork skills is essential.
• Willingness and ability to collaborate in a highly diverse, multi-disciplinary environment.
• Excellent oral and written communication skills necessary to effectively work in a multidisciplinary team environment.
• Communication and presentation skills to engage technical and non-technical audiences.
• Strong interpersonal abilities.
• Strong teamwork skills.
• Highly motivated to support research projects.

The University is a participating employer with Utah Retirement Systems (“URS”). Eligible new hires with prior URS service, may elect to enroll in URS if they make the election before they become eligible for retirement (usually the first day of work). Contact Human Resources at (801) 581-7447 for information. Individuals who previously retired and are receiving monthly retirement benefits from URS are subject to URS’ post-retirement rules and restrictions. Please contact Utah Retirement Systems at (801) 366-7770 or (800) 695-4877 or University Human Resource Management at (801) 581-7447 if you have questions regarding the post-retirement rules.
This position may require the successful completion of a criminal background check and/or drug screen.

The University of Utah values candidates who have experience working in settings with students and patients from all backgrounds and possess a strong commitment to improving access to higher education and quality healthcare for historically underrepresented students and patients.

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. The University does not discriminate on the basis of sex in the education program or activity that it operates, as required by Title IX and 34 CFR part 106. The requirement not to discriminate in education programs or activities extends to admission and employment. Inquiries about the application of Title IX and its regulations may be referred to the Title IX Coordinator, to the Department of Education, Office for Civil Rights, or both.
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

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