Postdoctoral Scientist, Multimodal Single Cell Foundation Models

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at https://www.jnj.com

Job Function:

Career Programs

Job Sub Function:

Post Doc – Data Analytics & Computational Sciences

Job Category:

Career Program

All Job Posting Locations:

Cambridge, Massachusetts, United States of America, La Jolla, California, United States of America, New Brunswick, New Jersey, United States of America, Spring House, Pennsylvania, United States of America

Job Description:

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
 

Johnson & Johnson Innovative Medicine is currently seeking a Postdoctoral Scientist, Multimodal Single Cell Foundation Models, a fixed-term position for 2-years, located at one of our sites in Spring House, PA, Cambridge, MA, New Brunswick, NJ, or San Diego, CA.
 

Key Responsibilities:

In this role, you will join the Data Science and Digital Health organization within Johnson and Johnson Innovative Medicine, focusing on leading the development of advanced network-based in silico immune/autoimmune disease models and/or neurodegenerative disease models. You will play a crucial role in identifying, characterizing and advancing therapeutic candidates for clinical development by providing innovative, multi-modal insights of complex biological regulation through the lens of computational modeling. Your responsibilities will include overseeing collaborations with multidisciplinary teams, driving model development, performing data analysis, and ensuring adherence to best practices in software engineering. You will work alongside biologists, immunologists and/or neuroscientists to convert their biological hypotheses into testable computational outcomes. Together, you will design and implement data-driven strategies to deepen our understanding of biological processes and disease mechanisms. Additionally, you will provide technical leadership, mentor junior scientists, and define research strategies to advance our understanding of various diseases and their underlying mechanisms.

In This Role, You Will:

• Collaborate with Translational Research, Discovery, and Development teams across therapeutic areas to develop AI/ML models that drive biological insights for personalized medicine.
• Analyze and integrate high-dimensional biological data from single-cell sequencing, spatial transcriptomics and other modalities for model training and validation.
• Develop and implement scalable statistical and machine learning algorithms by using large scale transcriptomics datasets.
• Participate in designing experiments that enable rigorous model evaluation alongside cross-functional teams.
• Have a strong background in training, fine-tuning, and deploying LLMs, as well as staying up-to-date with the latest advancements and research in the field, which is essential.
• Develop and deploy machine learning models and algorithms to analyze and extract insights from large, complex datasets across multiple modalities.
• Ensure the accuracy, reliability, and scalability of the machine learning models and algorithms developed.
• Collaborate with data engineering teams to ensure seamless integration and deployment of foundation models into production environments.
• Document and communicate best practices and workflows for applying LLM technology in multi-omics data analysis.
• Maintain compliance with internal coding standards, data integrity practices, and reproducibility protocols for research outputs.
• Communicate model performance and research findings effectively through technical reports, presentations, and contributions to peer-reviewed publications.

Qualifications:

• Ph.D. in computer science, artificial intelligenc