2026 Summer Intern - Patient Centered-Outcomes Research in Data Sciences and Analytics

Department Summary

This internship is in Patient-Centered Outcomes Research (PCOR), a core function within Product Development Data Sciences and Analytics that provides strategic leadership and scientific rigor across Development at Roche. PCOR collaborates in cross-functional teams on clinical trials, focusing on patients’ experiences with a disease or condition, e.g., symptoms, impacts on functioning or Health-Related Quality of Life (HRQOL), experience with treatment, preference for outcomes and treatments. 

HRQoL endpoints are crucial measures in clinical development, increasingly mandated by regulatory bodies like the FDA. The reliability of these measures depends entirely on the psychometric integrity of the Patient-Reported Outcome (PRO) questionnaires used. However, traditional psychometric validation (e.g., assessing cultural bias or measurement stability over time) is slow. This 12-week internship proposes an innovative solution by leveraging Large Language Models (LLMs) to serve as high-throughput synthetic semantic models and synthetic participants. The project’s dual focus is on robustifying Roche’s proprietary instruments and demonstrating a faster, data-driven approach to clinical trial planning.

Primary Focus: Assessing Questionnaire Robustness and Developing Guidelines: The core deliverable of this project is the creation of a Proposed Guideline/Protocol for LLM-based psychometric screening. This guideline will be built through practical application on a selected Roche-developed HRQoL questionnaire. 

Secondary Focus: Power Calculation Pilot: This phase involves validating the LLM's utility as a synthetic participant for clinical trial planning. A pilot study will generate synthetic patient data for a single high-priority HRQoL endpoint (e.g., Physical Functioning) across two trial arms and time points. The LLM-generated data will be analyzed to calculate the two critical inputs required for power calculations. 

This internship position is located in South San Francisco, on-site.  

The Opportunity

• Develop experience in statistical analysis of clinical trial data.

• Apply LLM to clinical trial data.

• Learn about the role of data sciences in drug development.

Program Highlights

• Intensive 12-weeks, full-time (40 hours per week) paid internship.

• Program start dates are in May/June 2026.

• A stipend, based on location, will be provided to help alleviate costs associated with the internship. 

• Ownership of challenging and impactful business-critical projects.

• Work with some of the most talented people in the biotechnology industry.

Who You Are (Required) 

Required Education:

You meet one of the following criteria:

• Must have attained a Master's Degree.

• Must be pursuing a PhD (enrolled student).

Required Majors: Statistics/Biostatistics, Psychometrics, Biomedical Informatics, and related fields.

Required Skills: 

• Understanding of statistical methods.

• Experience in Working knowledge of programming in R, and version control systems like Git.

Preferred Knowledge, Skills, and Qualifications

• Excellent communication, collaboration, and interpersonal skills.

• Complements our culture and the standards that guide our daily behavior & decisions: Integrity, Courage, and Passion.

• Basic knowledge of psychological measurement methods or Quality-of-Life research is desirable.

Relocation benefits are not available for this job posting. 

The expected salary range for this position based on the primary location of California is $40.00-$46.00 hour. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. This position also qualifies for paid holiday time off benefits.

Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.

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