Perform exploratory data analysis on large-scale proteomic datasets from public repositories (e.g., UK Biobank, GNPC) and internal J&J studies.
Conduct clustering of disease indications and patient subgroups based on autoantibody status.
Perform pathway enrichment analysis to identify biological processes linked to autoantibody generation.
Investigate whether proteomic signatures can predict autoantibody presence across different disease indications.
Summarize findings and contribute to early-stage predictive modeling approaches for autoantibody detection using proteomic or multi-omic data.

Requirements

Currently enrolled in a graduate or advanced undergraduate program in Computer Science, Bioinformatics, Data Science, or a related field.
Strong programming skills (e.g., Python, R) and experience with machine learning, statistical modeling, and data visualization.
Familiarity with proteomics analysis and large-scale biological datasets.
Knowledge of neuroscience or immunology is a plus but not required.
Ability to work independently and communicate findings effectively.
Permanently authorized to work in the U.S., must not require sponsorship of an employment visa (e.g., H-1B or green card) at the time of application or in the future.

Benefits

Co-Ops/Interns are eligible to participate in Company sponsored employee medical benefits in accordance with the terms of the plan.
Co-Ops and Interns are eligible for the following sick time benefits: up to 40 hours per calendar year; for employees who reside in the State of Washington, up to 56 hours per calendar year.
Co-Ops and Interns are eligible to participate in the Company’s consolidated retirement plan (pension).

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills

PythonRmachine learningstatistical modelingdata visualizationexploratory data analysispathway enrichment analysisproteomics analysispredictive modelingmulti-omic data

Soft skills

independent workeffective communication