Description

At Johnson & Johnson (J&J), we are on a mission to change the trajectory of health for humanity. Interventional Oncology (INTO) is a cross-sector R&D organization working within J&J that brings together pharmaceutical and medical device expertise with the aim to meaningfully alter the course of lung and adjacent cancers and improve patient outcomes.

We are looking for a 2024 Summer Intern in Biomarker Analytics for J&J Interventional Oncology. The location is flexible – Boston, Massachusetts or San Francisco, California is preferred with an option for remote.

As part of the Data Sciences team, the Summer Intern will coordinate and analyze molecular datasets, including RNA and DNA sequencing data, to improve understanding of disease biology, enable patient selection strategies, and evaluate response in lung cancer. The successful candidate will use statistical learning methods to identify robust and sparse biomarkers with multi-omics patient cohort datasets aligned to the therapeutic portfolio of INTO to facilitate a better understanding of treatment response, patient stratification, and future study design.

Key responsibilities include:

1. Conducting literature review to understand and evaluate published methods for biomarker discovery and validation
2. Cleaning and processing both internal and external multi-omics datasets for down-stream analysis
3. Understanding and implementing statistical models to derive biomarkers to predict treatment response
4. Collaborating and communicating results to an innovative team of cross-functional scientists (e.g., Data Sciences, Discovery and Translational Research, and Clinical Sciences)
5. Excellently documenting study design, analytical experiments, and findings
6. Providing clean, reproducible analysis code

Qualifications:

• The candidate must be currently enrolled in a PhD program in bioinformatics, biostatistics, or computational biology
• Hands-on experience with analysis of high-dimensional multi-omics data (e.g., RNA-seq and DNA-seq) and statistical learning models (e.g., linear model, classification and feature selection) is required
• Experience in using Python for the analysis of molecular data is required. Familiarity with R is a plus
• Excellent verbal and written communication skills are required
• Experience with projects involving 1) biomarker identification/validation, 2) association analyses using large datasets, and 3) large genomic patient cohort studies such as The Cancer Genome Atlas is highly preferred

Johnson & Johnson is an Affirmative Action and Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, or protected veteran status and will not be discriminated against on the basis of disability.

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