University of Chicago
Department
BSD CCC - Computational Oncology Unit
About the Department
Job Summary
Responsibilities
Applies and develops computational and bioinformatics approaches to process, analyze, interpret, and visualize complex oncology and biological datasets.
Develops, implements, and maintains bioinformatics workflows and pipelines to support cancer research and other computational biology projects. Evaluates existing approaches and modifies methods as needed to address specific research questions and data requirements.
Uses R, Python, and other applicable computational tools to perform statistical analyses, data processing, visualization, and interpretation of oncology and biological data.
Develops and applies algorithms, computational methods, and software solutions to identify, characterize, and classify biological features, patterns, and relationships within complex datasets.
Implements, modifies, and supports web-based bioinformatics tools and computational applications. Troubleshoots technical issues and identifies opportunities to improve functionality, efficiency, and usability.
Collaborates with investigators, computational scientists, research staff, and other multidisciplinary team members to understand research objectives, define analytic requirements, and develop appropriate computational approaches.
Supports the interpretation and communication of analytic results through the development of figures, visualizations, summaries, and other materials for research presentations, manuscripts, reports, and related scientific activities.
Performs quality control and validation of computational analyses, workflows, and outputs to support data accuracy, consistency, and reproducibility.
Maintains clear documentation of computational methods, code, pipelines, data processing procedures, and analytic outputs in accordance with established research and data management practices.
Stays current with emerging computational biology, bioinformatics, and data science methods and evaluates their potential application to ongoing oncology research.
Participates in creating data algorithms and specialized computer software to identify and classify components of a biological system (i.e. DNA and protein sequences).
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.
Work Experience:
Certifications:
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Preferred Qualifications
Education:
MS degree in computer science and bioinformatics.
Experience:
Experience using Python, Perl, or other programming languages for computational biology, bioinformatics, or biological data analysis.
Experience working in Unix/Linux environments and utilizing cloud or high-performance computing resources.
Experience analyzing high-throughput genomic datasets, including RNA sequencing, next-generation sequencing (NGS), whole-exome sequencing (WES), or Hi-C data.
Experience developing, implementing, or maintaining bioinformatics workflows and computational pipelines.
Experience with imaging informatics or analysis of imaging-related datasets.
Preferred Competencies
Strong analytical and problem-solving skills with the ability to evaluate complex biological data and develop appropriate computational approaches.
Proficiency in applicable programming and statistical analysis tools, including R and Python.
Knowledge of bioinformatics methods, computational biology principles, and genomic data analysis.
Knowledge of Unix/Linux environments and cloud or high-performance computing resources.
Strong attention to detail with the ability to develop, validate, document, and maintain accurate and reproducible computational workflows.
Strong organizational and communication skills with the ability to work independently and collaborate effectively with investigators, computational scientists, and multidisciplinary research teams.
Working Conditions
Office and research environment.
Requires extended periods of computer work and data analysis.
Requires the ability to work on multiple computational and research projects with competing priorities and deadlines.
May require occasional attendance at research meetings, presentations, or collaborative activities outside of the regular work location.
May require flexibility to meet research, project, or publication deadlines.
Application Documents
Resume (required)
Cover letter (preferred)
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When applying, the document(s) MUST be uploaded via the My Experience page, in the section titled Application Documents of the application.
Job Family
Role Impact
Scheduled Weekly Hours
Drug Test Required
Health Screen Required
Motor Vehicle Record Inquiry Required
Pay Rate Type
FLSA Status
Pay Range
The included pay rate or range represents the University’s good faith estimate of the possible compensation offer for this role at the time of posting.
Benefits Eligible
The University of Chicago offers a wide range of benefits programs and resources for eligible employees, including health, retirement, and paid time off. Information about the benefit offerings can be found in the Benefits Guidebook.
Posting Statement
The University of Chicago is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender, gender identity, or expression, national or ethnic origin, shared ancestry, 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.
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.
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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