Postdoctoral Scientist - Multimodal AI

Johnson & Johnson Innovative Medicine

3d • €60,000 - €96,255 • Hybrid

About The Position

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.

Requirements

• Ph.D. in Computational Biology, Bioinformatics, Computer Science, Biomedical Engineering, Applied Mathematics, Statistics, Electrical Engineering, or a related quantitative field.
• Strong expertise in machine learning, deep learning, foundation modeling, or related areas
• Demonstrated experience developing and evaluating machine learning methods for scientific or biomedical applications.
• Hands-on experience with Python and modern AI/ML frameworks and tools, such as PyTorch, JAX, Hugging Face, Git-based version control, Docker, Kubernetes, or equivalent technologies.
• Working knowledge of molecular and cellular biology, genetics, disease biology, or drug discovery, with the ability to connect computational findings to biological interpretation and experimental context.
• Experience analyzing at least one biomedical modality, such as transcriptomics, proteomics, single-cell omics, high-content imaging, tissue imaging, spatial biology, or other high-dimensional biological data.
• Ability to work effectively in multidisciplinary teams and communicate complex analytical findings to both technical and scientific stakeholders.
• Strong scientific communication skills, with the ability to present complex methods and findings clearly to technical and scientific audiences.

Nice To Haves

• Experience developing multimodal learning systems that integrate two or more biological data modalities.
• Experience with multimodal foundation models, self-supervised learning, contrastive learning, or generative modeling.
• Experience designing AI agents, multi-agent systems, or agentic workflows that support scientific reasoning, hypothesis generation, or experimental planning.
• Familiarity with retrieval-augmented generation, scientific copilots, or autonomous research systems that compile evidence from biomedical literature, databases, knowledge graphs, and experimental data.
• Experience supporting pharmaceutical R&D activities such as target identification, mechanism of action understanding, biomarker discovery, translational research, compound characterization, or precision medicine.
• Experience developing reproducible research software or contributing to shared AI/ML platforms.

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.
• Contribute to reusable AI platforms, software tools, and data foundations that enable enterprise-scale biomedical AI applications.
• Develop robust benchmarking strategies, establish strong baselines, and evaluate model generalizability, interpretability, and biological relevance.
• Lead end-to-end research activities, including study design, hands-on coding, model development and evaluation, technical documentation, progress reporting, and communication of findings.
• Document and disseminate research findings internally and externally, including through publications in leading AI, computational biology, and bioinformatics venues.

Benefits

• annual bonus
• vacation days
• parental leave for a minimum of 12 weeks
• bereavement leave
• caregiver leave
• volunteer leave
• well-being reimbursement
• programs for financial, physical and mental health
• service anniversary and recognition awards
• insurance plans

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree