Postdoctoral Scientist, In Silico Immune Disease Models (m/f/x) Full-time

Postdoctoral Scientist, In Silico Immune Disease Models

Johnson & Johnson Innovative Medicine is currently seeking a Postdoctoral Scientist, In Silico Immune Disease 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 leading the development of advanced network-based in silico immune/autoimmune 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 and immunologists to convert their biological hypotheses into testable computational outcomes. 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:

• Lead collaborations 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 using large-scale transcriptomics datasets.
• Oversee the design of experiments that facilitate rigorous model evaluation in collaboration with cross-functional teams.
• Ensure 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.
• Mentor junior researchers and provide technical leadership to enhance team capabilities and research output.

Qualifications:

• A recent Ph.D. degree within three years in computer science, artificial intelligence, software engineering, or a related field.
• Proficient in Python and C/C++.
• Demonstrated ability to design and implement reproducible workflows for large scale transcriptomics data analysis.
• Strong background in developing and optimizing machine learning algorithms. Knowledge graphs or ML-driven biological network modeling strongly preferred.
• Applying such algorithms and methods in a biological context. Molecular and immunological contexts strongly preferred.
• Proven track record of impactful research with publications in top-tier peer-reviewed journals.
• Experience in defining research strategies and setting project milestones to drive innovation in foundational models.
• Strong communication skills to present complex concepts clearly to both scientific peers and non-experts.

Preferred Qualifications:

• First-hand experience in oncology and/or immunology research.
• Knowledge of therapeutic strategies and clinical implications in cancer and immune-related diseases.
• Familiarity with multi-omics models and integrating data across multiple platforms.

R-028031