Postdoctoral Scientist - Multimodal AI

7555-Janssen Pharmaceutica NV Legal Entity; Geel; Sur place; EUR 60 000 - 96 000; Plein temps

Résumé du poste

Johnson & Johnson Innovative Medicine is seeking a Postdoctoral Scientist in Multimodal AI for Biomedical Discovery to advance AI/ML-enabled drug discovery. You will integrate imaging, transcriptomics, proteomics, structures, literature, and data to generate actionable insights guiding target discovery and translational biology.

Ideal candidates combine strong AI/ML expertise with biological knowledge and a commitment to scientific discovery in a collaborative, multidisciplinary environment.

Qualifications

• Ph.D. required in a quantitative field related to computational biology, bioinformatics, CS, or engineering.
• Strong expertise in machine learning, deep learning, foundation modeling, or related areas.
• Experience developing and evaluating ML methods for scientific/biomedical applications.
• Hands-on with Python and modern AI/ML frameworks (PyTorch, JAX, Hugging Face) and tools.
• Knowledge of molecular/cellular biology and drug discovery context.
• Experience analyzing biomedical modalities (transcriptomics, proteomics, imaging, etc.).
• Ability to communicate complex analyses to technical and scientific stakeholders.

Responsabilités

• Develop and evaluate multimodal AI/ML methods for diverse biomedical data.
• Design experiments and computational approaches to generate biologically meaningful hypotheses.
• Collaborate with biologists, chemists, computational biologists, statisticians, AI/ML scientists, and data scientists.
• Create scalable AI solutions by integrating heterogeneous evidence sources.
• Contribute to reusable AI platforms, tools, and data foundations for enterprise-scale apps.
• Establish benchmarking, baselines, and evaluate model generalizability and biological relevance.
• Lead end-to-end research activities from design to documentation and communication.
• Publish findings internally and externally in AI, computational biology, and bioinformatics venues.

Connaissances

Machine learning

Deep learning

Foundation models

Multimodal AI

Scientific communication

Team collaboration

Formation

Ph.D. in Computational Biology, Bioinformatics, Computer Science, Biomedical Engineering, Applied Mathematics, Statistics, Electrical Engineering, or a related quantitative field

Outils

Python

PyTorch

JAX

Hugging Face

Docker

Kubernetes

Git

Description du poste

Company Overview

At Johnson & Johnson,we believe health is everything. Our strength in healthcare innovation empowers us to build aworld where complex diseases are prevented, treated, and cured,where treatments are smarter and less invasive, andsolutions 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 jnj.com. As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.

Job Details

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.
• 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.

Qualifications

• Education: 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.

Preferred Skills

• 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.

EEO Statement

Johnson & Johnson is an affirmative action and equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, protected veteran status, or disability.

Salary and Benefits

The anticipated base pay range for this position is: €60,000.00 - €96,255.00

• In addition to base pay, we offer the following benefits*: an annual bonus with set target (% of pay) depending on pay grade / location, where the actual amount is based on the employees’ and companies’ performance of the previous calendar year, or sales commissions.
• Moreover, we offer 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.
• We also offer service anniversary and recognition awards, and subject to the terms of their respective plans, employees - and in some location’s eligible dependents - can participate in several insurance plans.
• For more information, visit Employee benefits | Supporting well‑being & career growth | Johnson & Johnson Careers. *This is for informative purposes only. Amounts and actual benefits may vary by location and are subject to change.

Company Closing Note

At Johnson & Johnson,we believe health is everything. Our strength in healthcare innovation empowers us to build aworld where complex diseases are prevented, treated, and cured,where treatments are smarter and less invasive, andsolutions 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/.