Senior Scientist, Computational Biology- Oncology Translational Research

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Job Function:
Discovery & Pre-Clinical/Clinical Development

Job Sub Function:
Translational Discovery & Development Biomarkers

Job Category:
Scientific/Technology

All Job Posting Locations:
Cambridge, Massachusetts, United States of America, La Jolla, California, United States of America, Spring House, Pennsylvania, United States of America

Job Description:

Senior Scientist, Computational Biology- Oncology Translational Research

About Innovative Medicine

Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements.

Visionaries like you work on teams that save lives by developing the medicines of tomorrow.

Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way.

Learn more at https://www.jnj.com/innovative-medicine

About Oncology

Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements.

Visionaries like you work on teams that save lives by developing the medicines of tomorrow.

Our Oncology team is focused on the elimination of cancer by discovering new pathways and modalities to finding treatments and cures.

We lead where medicine is going and need innovators with an unwavering commitment to results.

Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way.

Learn more at https://www.jnj.com/innovative-medicine

We are seeking a highly motivated senior scientist to join our translational research team based in Spring House, PA, Cambridge, MA, La Jolla, CA.

Position Summary

The Senior Scientist, Computational Biology- Oncology Translational Research, will be responsible for analysis, interpretation and integration of complex, multimodal omics, biomarker, and clinical data.

The individual will apply rigorous AI-enabled bioinformatics, statistical, and machine-learning approaches to generate insights that meaningfully inform oncology clinical development, while partnering closely with Translational Research Leaders, Clinical Development,...