Johnson & Johnson Innovative Medicine is currently seeking a Postdoctoral Scientist (F/M/X), Transcriptomics Foundation Models with a strong preference for this individual to be located at one of our sites in Berlin, Germany, Beerse, Belgium, Spring House, PA, Cambridge, MA, Titusville, NJ, or La Jolla, CA (Remote work options within the US may be considered on a case-by-case basis and if approved by the company).

Key Responsibilities:

In this role, you will join the Data Science and Digital Health organization within Johnson and Johnson Innovative Medicine, focusing on developing advanced foundation models using large scale single cell sequencing data. You will be pivotal in understanding the tumor microenvironment and its clinical implications by leveraging innovative algorithms and high-performance computing. Your responsibilities include collaborating with multidisciplinary teams, model development, data analysis, and ensuring adherence to best practices in software engineering.

In This Role, You Will:

• Collaborate with Translational Research, Discovery, and Development teams to develop AI/ML models that drive insights for personalized medicine.

• Analyze and integrate high-dimensional biological data from spatial transcriptomics and single-cell sequencing 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.

• 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:

• Recent Ph.D. (last 3 years) in computer science, artificial intelligence, bioinformatics, or a related field.

• Proficient in Python and C/C++.

• Strong background in developing and optimizing machine learning algorithms.

• Experience in modular software development with a focus on scalable, reusable code for AI systems.

• Deep knowledge of machine learning techniques and high-dimensional optimization.

• Experience analyzing large-scale transcriptomics datasets.

• Proven track record of impactful research with publications in top-tier peer-reviewed journals.

• Strong communication skills to present complex concepts clearly to both scientific peers and non-experts.

Preferred qualifications:

• Experience in oncology and/or immunology research.

• Familiarity with cell therapy discovery and development processes.

• Knowledge of therapeutic strategies and clinical implications in cancer and immune-related diseases.