At Johnson Spring House, PA, USA; Beerse, Belgium; or Madrid, Spain.
(No fully remote option.)
Please note that this role is available across multiple countries and may be posted under different requisition numbers to comply with local requirements.
While you are welcome to apply to any or all of the postings, we recommend focusing on the specific country(s) that align with your preferred location(s): USA - Requisition Number: R-** Belgium - Requisition Number: R-** Spain - Requisition Number: R-** Within DDSAI, our teams develop innovative solutions using a variety of data sources across multiple therapeutic areas.
We are looking for a highly motivated and innovative Postdoctoral Scientist to work at the intersection of advanced AI/ML modeling at scale, multimodal representation learning, drug discovery and predictive biology.
The successful candidate is self-motivated, creative, and an effective communicator, with a strong interest in deep learning for imaging microscopy and multi-omics.
The role focuses on developing advanced models that analyze and quantify the heterogeneity of perturbed cellular systems and integrate multi-scale biological data (e.g., high-content imaging, phenomics, transcriptomics, and proteomics) to derive new biological insights that support the next-generation portfolio for drug discovery.
A successful candidate should demonstrate a strong capacity to build, evaluate, and benchmark AI/ML methods, and publish findings in top-tier peer-reviewed publications.
Key Responsibilities * Conceive, design, develop, implement and validate innovative AI/ML solutions for drug discovery problems using multimodal data of perturbed cells.
* Analyze and extract novel biological insights from large-scale, heterogeneous high-dimensional data (e.g., imaging microscopy, phenomics, transcriptomics, proteomics).
* Develop and evaluate innovative computer vision solutions to quantify heterogeneity of perturbed cells.




* Collaborate closely with both internal and external cross-functional teams of scientists and engineers to advance algorithms and product development to improve project outcomes.
* Clearly communicate complex technical methodologies and present findings to diverse audiences and stakeholders to support informed decision-making.
* Follow standard processes for documentation and maintaining an up-to-date code repository.
* Draft manuscripts and disseminate research findings internally and externally (e.g., publishing in peer-reviewed conferences/journals).
Qualifications * Ph.D. in Electrical Engineering, Biomedical Engineering, Computer Science, Applied Mathematics, or a related major.
(PhD completed within the last 3 years or to be completed within the next 6 months.) * Strong technical expertise in AI/ML for biological applications, with excellent analytical skills in at least one domain area (representation learning, multimodal integration, computational biology, imaging microscopy) and a proven track record (publications in top-tier AI/ML conferences or journals).
* Experience developing foundation models and/or multimodal modeling of biological data in related applications, such as Cell Painting, imaging microscopy, and multi-omics.
* Solid working knowledge of deep-learning architectures and techniques (e.g., Transformers, CNNs, graph networks, self-supervised and multi-instance learning, etc.) and their application to multimodal representation learning, alignment, and fusion.
* Proficiency with one or more programming languages, preferably Python, and proficiency in one or more AI frameworks such as PyTorch or TensorFlow.
* Strong communication skills, with the ability to present analytical results on behalf of the project team in a multi-functional setting, contextualizing how the work fits within the broader project.
* This position will be based at any of the following locations: Cambridge, MA (preferred); Spring House, PA; Beerse, Belgium; or Madrid, Spain.
(No fully remote option.)
Johnson

📌 Postdoctoral Scientist (España)
🏢 Johnson & Johnson
📍 España