Postdoctoral Scientist - Multimodal AI

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Job Function:
Career Programs

Job Sub Function:
Post Doc - Data Analytics & Computational Sciences

Job Category:
Career Program

All Job Posting Locations:
Beerse, Antwerp, Belgium, Cambridge, Massachusetts, United States of America, Madrid, Spain, Spring House, Pennsylvania, United States of America

Job Description:

Johnson & Johnson Innovative Medicine Research & Development, Data, Data Science & AI organization, is recruiting a Postdoctoral Scientist in Multimodal AI for Biomedical Discovery to advance AI/ML-enabled drug discovery.

Our multidisciplinary organization develops innovative solutions using diverse biomedical data across disease areas.

We are seeking a highly motivated Postdoctoral Scientist to work at the intersection of machine learning, computational biology, multimodal foundation models, and scientific AI.

The successful candidate will develop next-generation AI systems that integrate imaging, transcriptomics, proteomics, molecular structures, scientific literature, and other biomedical data to generate actionable insights for target discovery, translational biology, disease mechanisms, and drug development.

The ideal candidate will combine strong AI/ML expertise with a solid understanding of biological systems and a commitment to advancing AI-enabled scientific discovery.

Key Responsibilities:


* Develop and evaluate multimodal AI/ML methods, including foundation models, predictive models, and generative approaches, for diverse biological data such as high-content imaging, transcriptomics, proteomics, molecular structures, preclinical and clinical assays, scientific literature, and knowledge bases.


* Design computational approaches that generate biologically meaningful hypotheses, inform experimental design, identify mechanisms of disease, and support target or compound prioritization.


* Partner with biologists, chemists, computational biologists, biostatisticians, AI/ML scientists, and data scientists to translate scientific questions into scalable AI solutions.


* Develop workflows that integrate heterogeneous evidence sources and support rigorous, transparent scientific decision-making.


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