Department

BSD CCC - Computational Oncology Unit

About the Department

The University of Chicago Comprehensive Cancer Center (UCCCC) is an integral component of the Biological Sciences Division (BSD). The BSD is the largest of four Divisions of the University and includes the Pritzker School of Medicine. UCCCC administers four established scientific programs, and the NCI-sponsored Cancer Center Support Grant provides funding for ten Shared Resources. The Comprehensive Cancer Center is comprised of over 150 faculty members from twenty departments with members currently being awarded over $47 million in total direct costs in peer-reviewed cancer research grants, and $28 million in non-peer reviewed grants and contracts. The activities of the Center are broad and varied, including research, training and education, communications, fundraising, marketing, clinical trials management and community outreach.

UCCCC has one of the largest cancer clinical trials programs in the country and in the Chicago area with nearly 500 adult and pediatric therapeutic trials actively accruing patients. Many of these studies are investigator-initiated, including Phase I or I/II trials, demonstrating UCCCC commitment to translate basic research findings to the clinic through proof-of-principle and early phase studies. UCCCC opens over 250 new trials each year and accrues approximately 900 participants to therapeutic trials each year.

Job Summary

As a Computational Oncology Programmer, you will be responsible for developing software to support big/multidimensional data acquisition, ingestion, and integration for research projects. You will design user interfaces and scalable back-end services, and your work will contribute to the innovative use of spatial data. You will be part of the COU initiative, and your role will require significant experience in bioinformatics software development.

Responsibilities

• Help with grant proposals by contributing sections describing the interplay between research objectives and new or expanded data resources.

• Participate in tools development, providing professional assistance in designing front-end applications and database systems' back-end schema.

• Analyze high-level system specifications and ensure that all application development standards are met.

• Develop and present technical training materials and web-based documentation, and ensure timely systems support and updates.

• Assist in conducting assessments and risk analysis of the computing environment.

• Evaluate past and present technologies to help develop new tools and ensure that all new tools have been through quality control reviews.

• Perform other related tasks as delegated by the director of the COU.

• Applies basic application of computational tools and information technology to gather, analyze and visualize data in biology and biomedical research.

• Interprets data analysis of high throughput genomics, proteomics and genetic data.

• Performs other related work as needed.

Minimum Qualifications

Education:

Minimum requirements include a college or university degree in related field.

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Work Experience:

Minimum requirements include knowledge and skills developed through 2-5 years of work experience in a related job discipline.

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Certifications:

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Preferred Qualifications

Education:

• MSC or Ph.D. in Information Sciences, Computer Science, Bioinformatics, or a related field.

Experience:

• Experience in programming using R, Python, and Perl programming languages with a proven history of software development.

Technical Skills or Knowledge:

• Demonstrated hands-on experience in developing Machine learning and Artificial intelligence algorithms.

• Deep statistical knowledge and experience performing statistical inference analysis.

• Experience and general proficiency using one or more high-level analysis tools or statistical languages (e.g., R, MATLAB, etc.).

• Computing experience using Python and R.

• Experience developing friendly UIs (using Rshiny, Java Script,…).

• Fluency in data organization, manipulation, and analysis.

• Experience in a UNIX/Linux-based environment.

• Experience with parallel processing and cloud computing services.

Preferred Competencies

• Understand and translate researchers' scientific goals into computational requirements.

• Identify and gain expertise in appropriate new technologies and software tools.

• Function as part of an interactive team while demonstrating self-initiative to achieve projects’ goals and COU's mission.

• Strong analytical skills and problem-solving ability.

Application Documents

• Resume (required)

• Cover letter (preferred)

Job Family

Research

Role Impact

Individual Contributor

FLSA Status

Non-Exempt

Pay Frequency

Biweekly

Scheduled Weekly Hours

15

Benefits Eligible

No

Drug Test Required

No

Health Screen Required

No

Motor Vehicle Record Inquiry Required

No

Posting Statement

The University of Chicago is an Affirmative Action/Equal Opportunity/Disabled/Veterans and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender, gender identity, national or ethnic origin, age, status as an individual with a disability, military or 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.

We seek a diverse pool of applicants who wish to join an academic community that places the highest value on rigorous inquiry and encourages a diversity of perspectives, experiences, groups of individuals, and ideas to inform and stimulate intellectual challenge, engagement, and exchange.

All offers of employment are contingent upon a background check that includes a review of conviction history. A conviction does not automatically preclude University employment. Rather, the University considers conviction information on a case-by-case basis and assesses the nature of the offense, the circumstances surrounding it, the proximity in time of the conviction, and its relevance to the position.

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