University of Colorado Anschutz Medical Campus 

Department: Radiology

Job Title: Information Sciences Professional (Intermediate, Senior, Principal -- Open Rank), part-time (0.2 FTE; qualification dependent)

Position #: 00846872 – Requisition #:39640

Job Summary:

Nature of Work

Information Science Professionals utilize applied or computational mathematical analyses for a wide array of different applications and to solve complex problems. Experiments may include text interpretation, coding, ground theory methodology for the analysis of certain data, and quantum state analyses. Information Science Professionals may also perform duties in labs that use primarily electronic equipment.

This Information Science Professional will be operating as a Machine Learning (ML) Engineer to help the Department of Radiology create artificial intelligence analysis of medical images. Working under the Principal Investigator (PI), Dr. Bennett Chin. The ML Engineer will be assisting with the creation of machine learning models and retraining systems using radiology data. To do this job successfully, the candidate will need exceptional skills in mathematics and programming; knowledge of data science and experience with software engineering is desired. The ultimate goal of this position will be to shape and build efficient deep learning applications.

This is a part-time, 0.2 FTE, position with an option to work remotely.

Examples of Duties Performed

Intermediate Level:

• Collaborate with and support Principal Investigators (PI) and other stakeholders in the area of  bioinformatics and data analysis

• Perform scientifically rigorous data management and bioinformatic analyses.

• Run machine learning tests and experiments.

• Computer System software maintenance and security.

• Assist with selection of appropriate datasets and data representation methods.

• Perform evaluation and analysis of test results.

• Train and retrain systems when necessary.

• Develop and disseminate a variety of tools designed to access relevant clinical and sample data

• Develop machine learning applications according to requirements.

• Research and implement appropriate ML algorithms and tools.

• Develop and implement complex analyses pipelines, programming, and data visualization techniques

• Extend existing ML libraries and frameworks.

• Creatively and effectively integrate data from multiple sources to accelerate discoveries

• Study and transform data science prototypes.

• Assist with the design and development of major bioinformatics-related programming projects

• Write custom scripts to access databases and analyze data

• Keep abreast of developments in the field.

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