Postdoctoral Scientist
Johnson & Johnson Innovative Medicine
Cambridge, MA0–5 yrs4h agovia LinkedIn
This job at a glance
- Who can apply
- New grads and up to 5 years
- Must know
- Machine learningComputer visionData structures & algorithmsStakeholder managementPythonPyTorch
- Nice to have
- Spring
- Work
- Remote
- Pay
- Not stated by the employer.
- Skill demand
- Machine learning20%Stakeholder management18%Data structures & algorithms12%Computer vision2%of 99 similar entry-level jobs posted in the US this week
- Listed
- Oct 29, 2026 · still open
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About the Role
Johnson & Johnson Innovative Medicine is seeking a Postdoctoral Scientist – Multimodal Representation Learning for Predictive Biology for a two-year fixed term position within the Data, Data Science & Artificial Intelligence (DDSAI) organization. This role will focus on advancing AI/ML analytics and multimodal modeling for drug discovery.
Location Options: Cambridge, MA (preferred); Spring House, PA; Beerse, Belgium; or Madrid, Spain. (No fully remote option.)
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 internal and external cross-functional teams of scientists and engineers to advance algorithms and product development.
- Clearly communicate complex technical methodologies and present findings to diverse audiences and stakeholders.
- 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).
Requirements & Tech Stack
- Strong technical expertise in AI/ML for biological applications.
- Excellent analytical skills in at least one domain area: representation learning, multimodal integration, computational biology, imaging microscopy.
- 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 learning, multi-instance learning).
- Proficiency with one or more programming languages, preferably Python.
- Proficiency in one or more AI frameworks such as PyTorch or TensorFlow.
- Strong communication skills, with the ability to present analytical results in a multi-functional setting.
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.