Postdoc: Multimodal AI for Drug Discovery

Johnson Johnson; United States; On-site; USD 70,000 - 120,000; Full time

Job summary

Johnson & Johnson Innovative Medicine is seeking a highly motivated Postdoctoral Scientist to advance AI/ML methods for predictive biology and multimodal representation learning in drug discovery. You will work on heterogeneity analysis of perturbed cells using high-content imaging, omics data, and multi-scale biological information to guide next-generation portfolios.

The role emphasizes developing scalable AI/ML models, publishing findings, and collaborating with internal and external teams.

Qualifications

• Ph.D. in Electrical Engineering, Biomedical Engineering, Computer Science, or related field (recent).
• Strong expertise in AI/ML for biological applications; experience in representation learning, multimodal integration, or computational biology.

Responsibilities

• Conceive, design, develop, implement and validate AI/ML solutions for drug discovery using multimodal data.
• Analyze large-scale heterogeneous data (imaging, phenomics, transcriptomics, proteomics).
• Develop and evaluate computer vision methods to quantify cell heterogeneity.
• Collaborate with cross-functional teams to advance algorithms and product development.
• Communicate complex methodologies clearly to diverse audiences and stakeholders.
• Maintain up-to-date code repositories and documentation.
• Draft manuscripts for internal and external dissemination.

Skills

AI/ML

Multimodal learning

Representation learning

Biological data analysis

Imaging microscopy

Education

Ph.D. in Electrical Engineering

Tools

Python

PyTorch

TensorFlow

R

Linux

Job description

Johnson & Johnson Innovative Medicine is seeking a highly motivated Postdoctoral Scientist to advance AI/ML methods for predictive biology and multimodal representation learning in drug discovery. You will work on heterogeneity analysis of perturbed cells using high-content imaging, omics data, and multi-scale biological information to guide next-generation portfolios.

The role emphasizes developing scalable AI/ML models, publishing findings, and collaborating with internal and external teams.