Computational Scientist

Job description

Hyde Park Campus

85658 Office Of VP Research

About the Unit
The University of Chicago Research Computing Center (RCC), a unit in the Office of Research and National Laboratories (RNL), provides high-end research computing resources to researchers at the University of Chicago. It is dedicated to enabling research by providing access to centrally managed High Performance Computing (HPC), storage, and visualization resources. These resources include hardware, software, high-level scientific and technical user support, and the education and training required to help researchers make full use of modern HPC technology and local and national supercomputing resources. The Office of Research and National Laboratories oversee the conduct of sponsored research, research program development, multi-institutional research institutes, national laboratory board, and contract management functions. RNL supports the development and coordination of research-related communications and educational programs at The University of Chicago. RNL oversees the management of two Department of Energy contracts for Argonne National Laboratory and Fermi National Accelerator Laboratory. When combined with the Lab R&D budgets, the office oversees approximately $1.4 billion in sponsored research. RNL works closely with individual scholars, departments, and divisions to encourage, seed, and coalesce research across the University, Argonne, and Fermilab campuses.

Job Information

Job Summary:

The Research Computing Center and MRI Research Center at The University of Chicago are working together on a project to investigate the early detection of prostate cancer using multi-parametric MRI (mpMRI) imaging and quantitative MRI. A computational scientist with experience in machine learning is needed to implement deep learning tools for deep learning computer-aided diagnostic systems that will demonstrably help clinicians to get the best possible prostate cancer diagnosis from mpMRI. Research activities will be to focus on MRI, although other imaging modalities will likely be employed to provide complimentary information.

This is a one-year position, if additional funding is secured the position may continue beyond one year.


  • Serve as a central knowledge resource for faculty and researchers;
  • Develop automatic multi-object segmentation, quantitative imaging biomarkers, and multivariate analysis methods using a massive MRI database.
  • State-of-the-art deep learning models will be continuously evaluated and implemented in a clinical prototype for validation and feedback. Results will be presented at scientific meetings and published in journals.
  • Data analysis methods will focus on the application of pattern recognition/machine learning/deep reinforcement techniques to analyze these multi-parametric data sets;
  • Demonstrate the developed artificial intelligence applications in automated prostate segmentation and in cancer detection using multi-parametric MRI imaging.
  • Help faculty with grant proposals by contributing sections describing the interplay between research objectives and new or expanded data resources.
  • Perform other duties as assigned.

  • Ability to understand and translate researchers' scientific goals into computational requirements.
  • Ability to work well with faculty and researchers.
  • Ability to identify and gain expertise in appropriate new technologies and/or software tools.
  • Ability to function as part of an interactive team while demonstrating self-initiative to achieve project's goals and Research Computing Center's mission.
  • Strong analytical skills and problem solving ability.

Additional Requirements

Education, Experience or Certifications:

  • Master's degree in computer science, computer engineering, data science, or similar required. A Ph.D. strongly preferred.

  • Background in machine learning and deep reinforcement learning, and with clear interest in image analysis required
  • Experience with deep learning frameworks, such as Keras, mxnet, scikit-learn is required

Technical Knowledge or Skills:
  • Software experience with Python and/or C++ required;
  • Strong computational image processing and visualization skills required;
  • Experience with MRI is strongly preferred.
  • Perform other duties as assigned.

Required Documents:
  • Cover letter
  • Resume

NOTE: When applying, all required documents MUST be uploaded under the Resume/CV section of the application

Benefit Eligibility

Pay Frequency

Pay Range
Depends on Qualifications

Scheduled Weekly Hours


Job is Exempt?

Drug Test Required?

Does this position require incumbent to operate a vehicle on the job?

Health Screen Required?

Posting Date

Remove from Posting On or Before

Posting Statement:

The University of Chicago is an Affirmative Action/Equal Opportunity/Disabled/Veterans Employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national or ethnic origin, age, status as an individual with a disability, protected veteran status, genetic information, or other protected classes under the law. For additional information please see the University's Notice of Nondiscrimination.

Staff Job seekers in need of a reasonable accommodation to complete the application process should call 773-702-5800 or submit a request via Applicant Inquiry Form.

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Full time

About Us
The University of Chicago is an urban research university that has driven new ways of thinking since 1890. Our commitment to free and open inquiry draws inspired scholars to our global campuses, where ideas are born that challenge and change the world.

We empower individuals to challenge conventional thinking in pursuit of original ideas. Students in the College develop critical, analytic, and writing skills in our rigorous, interdisciplinary core curriculum. Through graduate programs, students test their ideas with UChicago scholars, and become the next generation of leaders in academia, industry, nonprofits, and government.

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Job No:
Posted: 12/1/2018
Application Due: 1/30/2019
Work Type: