Senior Biomedical Informatics Programmer

The University of Chicago; Chicago (IL); On-site; USD 100,000 - 150,000; Full time

Job summary

The University of Chicago invites applications for a Senior Biomedical Informatics Programmer in the Precision Health Informatics Lab (PHIL). You will design, optimize, and maintain production-grade pipelines linking genomic, phenotypic, and clinical data to support gene-disease discovery at scale.

Collaborate with scientists and clinicians to ensure reproducible results, develop scripts and tools, and contribute to biobank-scale analyses including GWAS and PheWAS.

Qualifications

• 7+ years of work experience in biomedical informatics or related field.
• Advanced degree (MS/PhD) preferred in bioinformatics, CS, or related area.
• Experience building production data pipelines and analyzing genomic/EHR data formats.

Responsibilities

• Design, optimize, and maintain production-grade pipelines for gene-disease analyses.
• Develop computable phenotype algorithms and integrate diverse data sources.
• Support biobank-scale studies and collaborate across multidisciplinary teams.
• Create reusable software tools and scripts for genomic analyses.
• Ensure pipelines are reliable, reproducible, and scalable.

Skills

Python

R

Data pipelines

Big data analysis

Education

Bachelor's degree

MS/PhD preferred

Tools

Python

R

VCF

FHIR/OMOP

PheWAS/GWAS

Job description

DepartmentBSD MED - General Internal Medicine

About the Department

The Precision Health Informatics Lab (PHIL), led by Dr. Joshua Denny, MD, MS, develops and applies computational and informatics methods to translate large-scale genomic and clinical data into actionable insights about human health and disease. The lab's work sits at the intersection of genomics, electronic health record (EHR) data, and population-scale biobank research, with a focus on discovering gene-disease relationships, characterizing the clinical effects of genetic variation, and enabling precision medicine applications. A growing part of this work involves machine learning, large language models, and generative AI, which the lab uses to extract identify patterns across heterogeneous data sources and accelerate the pace of genomic discovery.

A central focus of the lab is phenomics, the integrative use of EHR-derived and survey-based phenotype data to power genetic and multiomic discovery. The lab develops and applies methods such as phenome-wide association studies (PheWAS), which test genetic variants against the full breadth of clinical phenotypes captured in health records, as well as traditional genome-wide association study (GWAS) approaches on complex phenotypes. PHIL builds and maintains computable phenotype algorithms, reproducible, data-driven definitions of disease states, drug effects, and other clinical conditions, that integrate EHR data, survey responses, and other health data sources.

We also seek to use large scale biobank data to uncover novel gene functions and previously unrecognized genetic diseases, an undertaking that depends on integrating genomic data with clinical, phenotypic, and knowledge-base resources at scale. PHIL collaborates broadly with clinical, genomic, and computational investigators to support biobank-scale studies, and is building a team of programmers, analysts, and scientists to sustain and expand this work.

Job Summary

The Senior Biomedical Informatics Programmer is integral to the ongoing operations of the Precision Health Informatics Lab (PHIL), providing critical scientific and bioinformatics programming support to enable large-scale biobank studies. This role will design, optimize, and maintain production-grade pipelines that connect genomic, phenotypic, and clinical data to support gene-disease discovery at scale, including studies using deep clinical characterization of individuals with rare genetic variants to uncover novel gene functions and genetic diseases.

Responsibilities

• Optimize and maintain best-practice pipelines for gene-disease association analyses, including genome-wide association studies (GWAS) and phenome-wide association studies (PheWAS).
• Build and refine computable phenotype algorithms for diseases, drug effects, and other clinical conditions by integrating EHR data with survey-based data sources.
• Develop scripts, pipelines, and software to analyze diverse health-related datasets, combining data across orthogonal sources - including EHR data, environmental exposures, and taxonomic/knowledge resources such as OMIM, the Human Phenotype Ontology, and DrugBank - to support genomic analyses.
• Provide broad-based programming and analytic support across a range of informatics and genomics research projects, including custom script development for analysis of public datasets and lab-generated data.
• Support the computational infrastructure underlying studies of rare genetic variants, helping enable discovery of novel gene functions and genetic diseases through clinical characterization.
• Collaborate with scientists, clinicians, and analysts to ensure pipelines are reliable, reproducible, and scalable for biobank-level data volumes.
• Generate public use resources.
• Lead implementation or modification of existing web-based bioinformatics tools.
• Provides expertise to biomedical informatics related concepts, applications, and tools.
• Performs other related work as needed.

Minimum Qualifications

• Education: Minimum requirements include a college or university degree in related field.
• Work Experience: Minimum requirements include knowledge and skills developed through 7+ years of work experience in a related job discipline.
• Certifications: —.

Preferred Qualifications

• Education: Advanced degree (MS or PhD preferred) in bioinformatics, computer science, computational biology, or related field.
• Experience: Strong programming skills (e.g., Python, R, or similar) and experience building production data pipelines.
• Experience with genomic and/or EHR data formats and analysis (e.g., VCF, FHIR/OMOP, PheWAS/GWAS methods).
• Familiarity with biomedical ontologies and knowledge bases (OMIM, HPO, DrugBank).
• Experience working with large-scale biobank or clinical datasets.
• Preferred Competencies: Excellent verbal and written communication skills.
• Excellent interpersonal and customer service skills.
• Excellent organizational skills, ability to maintain files.
• Proficiency with word processing applications, preparing presentations, spreadsheets and databases.
• Ability to maintain calm and courteous demeanor and to work productively despite heavy workload, competing priorities, complex problems, and tight deadlines.
• Ability to exercise sound judgment and excellent problem-solving skills.
• Ability to exercise flexibility and contribute to the overall work of the team.
• Considerable skill in working both independently and as a team member.
• Ability to take initiative.

Resume/CV (required)

Cover Letter (required)

The University of Chicago uses AI-assisted tools to streamline and augment some recruitment processes; however, AI is not used to make hiring decisions.

Job Family: Research

Role Impact: Individual Contributor

Scheduled Weekly Hours: 40

Drug Test Required: No

Health Screen Required: No

Motor Vehicle Record Inquiry Required: No

Pay Rate Type: Salary

FLSA Status: Exempt

Pay Range: $100,000.00 - $150,000.00

The included pay range represents the University's good faith estimate of the possible compensation offer for this role at the time of posting.

Benefits

Eligible: Yes

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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