Postdoctoral Scientist - Multimodal Representation Learning for Predictive Biology

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

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

Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements. Visionaries like you work on teams that save lives by developing the medicines of tomorrow.

Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way.

Learn more at https://www.jnj.com/innovative-medicine

Johnson & Johnson Innovative Medicine is recruiting for a Postdoctoral Scientist - Multimodal Representation Learning for Predictive Biology to join the Data, Data Science & Artificial Intelligence (DDSAI) organization for a two-year fixed term position, helping advance AI/ML analytics and multimodal modeling for drug discovery. 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.)

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-094412

Belgium - Requisition Number: R-095646

Spain - Requisition Number: R-095648

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 jour