Bioinformatics Intern

Job Title: Bioinformatics Intern

Location: Hybrid (Daly City, CA)
Duration: Summer 2026 (12 weeks)

About Us

PinkDx is an early-stage diagnostics company focused on improving care for women. We’re developing non-invasive approaches to help patients and physicians get faster, clearer answers to cancer-related symptoms. Our work sits at the intersection of biology, next-generation sequencing (NGS), and machine learning/AI. We’re a highly collaborative, fast-moving team where everyone makes meaningful contributions that directly impact patients’ lives.

Role Overview

We are seeking a summer intern to join the Data Science team to evaluate and improve the robustness of our NGS-based assays and machine learning approaches. This role is ideal for someone interested in working with high-dimensional NGS data to generate meaningful insights that guide product development decisions. You’ll gain hands-on experience in an industry R&D setting, receive close mentorship, and have opportunities to share your work with a broader team.

What You’ll Do

• Apply statistical and machine learning methods to explore biological and clinical datasets
• Support the design, execution, and interpretation of in-silico simulation studies to evaluate assay and model performance under different conditions
• Assist in developing and evaluating approaches for quality control and performance assessment
• Explore and prototype novel bioinformatics approaches to improve NGS-based diagnostic assays
• Visualize and communicate results through presentations for both technical and non-technical audiences

Qualifications

• Current Master's student or PhD candidate in a scientific or quantitative field (e.g., Bioinformatics, Computational Biology, Statistics, Genetics, etc.).
• Hands-on experience working with RNA-seq or other high dimensional NGS data
• Familiarity with bioinformatics pipelines from raw sequencing data to downstream outputs (e.g., FASTQ/BAM processing, alignment, QC)
• Understanding of common RNA-seq QC metrics and their application to experimental troubleshooting and assay evaluation.
• Proficiency in scripting languages such as R or Python (R preferred), and experience working in Linux environments and high-performance computing clusters (e.g. Slurm).
• Strong communication skills and ability to collaborate effectively with cross-functional teams.

Preferred Qualifications

• Experience developing machine learning models using high dimensional biological data
• Familiarity with basic genomics wet-lab concepts (DNA/RNA extraction, PCR, next-generation sequencing).