University of Utah

Department 00810 - Scient Comp & Imag Instit-Oper Job Summary

Job Summary

The Scientific Computing and Imaging (SCI) Institute at the University of Utah invites applications for one full-time (1.0 FTE) research software engineer to design, develop, optimize, and deploy deep learning solutions for large-scale medical images to automate various medical imaging tasks to support scientific and application-driven research. The SCI Institute looks for highly talented, motivated, disciplined research software engineers with professional experience and interest in state-of-the-art image analysis and machine learning technologies. We are seeking committed researchers who have demonstrated ability to work effectively and independently with minimal supervision within a multi-disciplinary research environment. This position is a perfect fit for individuals with a background in research. Still, they love to write code, thrive in an environment of cutting-edge science in academia, and apply their programming expertise to compelling research problems.

Why Join Us

This role offers an exciting opportunity to work at the intersection of deep learning and medical science, developing tools that directly impact patient care and clinical workflows. Our team provides a supportive, collaborative environment where innovation is encouraged, and your contributions will have a tangible impact on advancing healthcare technology. The successful candidate will enjoy being part of a world-renowned research institute and working closely with graduate students, post-doctoral researchers, software developers/engineers, research scientists, and faculty members to develop cutting-edge tools.

The SCI Institute

The Scientific Computing and Imaging (SCI) Institute at the University of Utah is an internationally recognized leader in visualization, scientific computing, and image analysis applied to a broad range of domains. The SCI Institute brings together faculty in bioengineering, computer science, mathematics, and electrical engineering in applying advanced computing technologies to challenges in a variety of domains, including biology and medicine. The SCI Institute includes 19 faculty members and over 200 other scientists, administrative support staff, and graduate and undergraduate students.

The overarching goals of the SCI Institute’s scientific computing research are to create new techniques, tools, and systems, by which scientists may solve problems affecting various aspects of human life. We believe that to advance the state-of-the-art and create meaningful computational solutions for such complex systems, one needs to advance research in a number of areas within scientific computing, including image analysis, visualization, simulation, and modeling. The SCI Institute presents a highly challenging, collaborative work environment that can be deeply rewarding for the right individual.

At the SCI Institute, we offer flexible working hours, the potential for career development and personal growth, diversity of work, and interaction with students. We also foster and support the sense of community among principal investigators, software engineers, and researchers in a collaborative environment. Furthermore, the University of Utah offers a competitive benefits package. Further information is available at http://www.sci.utah.edu/.

Opportunities for Professional Development

The successful candidate will have the opportunity to develop their research, publication, and presentation skills under mentorship from established faculty investigators. In addition, successful candidate will benefit from mentoring activities at the SCI Institute and Kahlert School of Computing (KSoC) to prepare them for the next phase of their careers. Through the Cyberinfrastructure Professionals (CIP) Cooperative (Co-Op) at the SCI Institute, successful candidate will access a community of research computing and data experts working together to support and sustain SCI’s world-class research efforts. Successful candidate will also have the opportunity to join the Future Faculty Fellow Program offered by the KSoC. This program trains postdoctoral candidates in elements needed for an academic career as researcher, teacher, mentor, and computing citizen. Professional development opportunities, including training in teaching, are also available on campus through the Office of Postdoctoral Affairs (https://postdocs.utah.edu).

Work Environment

• You will be contributing to cutting-edge computational methods for image analysis.
• We offer flexible working hours.
• We offer professional career development opportunities.
• The University of Utah offers a very competitive benefits package.

Benefits

• Health, dental, and wellness coverage https://www.hr.utah.edu/benefits/health\_wellness.php – Free public transportation pass (https://commuterservices.utah.edu/uta/) (Utah Transit Authority) – Paid leave time (https://www.hr.utah.edu/benefits/paidLeave.php)
• Tuition reduction for employee and family members (https://www.hr.utah.edu/benefits/tuition.php) – and more: https://www.hr.utah.edu/benefits

Location

The SCI Institute is a world-class research institute located within the Warnock Engineering Building on the University of Utah campus, located in Salt Lake City, Utah, the hub of many emerging tech start-ups. Surrounded by stunning mountain views and fantastic hiking and

camping destinations just 20 minutes outside the city, Salt Lake is an excellent place for networking in tech and outdoor activities.

Responsibilities

• 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.

This job description is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities and qualifications required of employees assigned to the job.

Work Environment and Level of Frequency typically required

Nearly Continuously: Office environment.

Physical Requirements and Level of Frequency that may be required

Nearly Continuously: Sitting, hearing, listening, talking.

Often: Repetitive hand motion (such as typing), walking.

Seldom: Bending, reaching overhead.

Minimum Qualifications

Requires a bachelor’s degree in a related area or equivalency (one year of education can be substituted for two years of related work experience) and 3-5 years of experience in the field or in a related area.

Applicants must demonstrate the potential ability to perform the essential functions of the job as outlined in the position description.

Preferences

Preferred Expertise

• 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.

Nice-to-Have

• 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.

Non-Technical Skillls

• 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.

Additional Information

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

https://safety.utah.edu/safetyreport This report includes statistics about criminal offenses, hate crimes, arrests and referrals for disciplinary action, and Violence Against Women Act offenses. They also provide information about safety and security-related services offered by the University of Utah. A paper copy can be obtained by request at the Department of Public Safety located at 1658 East 500 South.

Read Full Description