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J&J Family of Companies Principal Scientist, Generative Biologics Design and Optimization in La Jolla, California

Principal Scientist, Generative Biologics Design and Optimization - 2306152908W


Janssen Research & Development, L.L.C., a division of Johnson & Johnson's Family of Companies is recruiting for a Principal Scientist , Generative Biologics Design and Optimization , located in Spring House, PA, Cambridge, MA, San Diego, CA or South San Francisco, CA. Remote work options may be considered on a case-by-case basis and if approved by the Company.

At the Janssen Pharmaceutical Companies of Johnson & Johnson, we are working to build a world without disease. Transforming lives by finding new and better ways to prevent, intercept, treat and cure disease inspires us. We bring together the best minds and pursue the most promising science. We are Janssen. We collaborate with the world for the health of everyone in it. Learn more at www.janssen.com and follow us @JanssenGlobal. Janssen Research & Development, LLC is part of the Janssen Pharmaceutical Companies.

This is a technical position in the Integrated Platform Optimization team within the In Silico Discovery organization, which provides computational support to accelerate and enhance discovery of the best drug candidates across all therapeutic modalities. This role will specifically interact with several functional groups across the Biologics Discovery organization to support the discovery and optimization of protein-based therapeutics. The successful candidate will work collaboratively between our functional groups and across organizations, including Biologics Discovery and Data Sciences, to develop deep generative modeling platforms that leverage large-scale datasets to accelerate our protein engineering and optimization workflows.



  • Ph.D. in Computer Science, Bioinformatics, Computational Biology or related field with at least 5 years of experience directly applied to problems in the Biotechnology and Pharmaceutical sectors.

  • Proven track record of leveraging tools from generative deep learning (e.g. CNNs, VAEs, GANs) to analyze complex data structures; practical experience with transfer learning and fine-tuning.

  • Deep understanding of protein structure-function relationships and direct experience applying state-of-the-art transformer-based architectures for protein structure prediction.

  • Strong working knowledge of diffusion-based models for structure-enabled protein design.

  • Proficient in building customized deep learning models using libraries such as PyTorch, Keras/TensorFlow in a scalable HPC environment; direct experience with cloud-based and GPU-accelerated compute platforms.

  • The preferred location for this position is Spring House, PA or Cambridge, MA. Consideration may be given for this position to be located in San Diego (La Jolla), CA, or South San Francisco, CA. Remote work options may be considered on a case-by-case basis and if approved by the Company. Travel up to 10% may be required.


  • Ability to work in matrixed teams, excellent interpersonal skills.

  • Excellent organization and communication skills, with the ability to convey complex computational concepts effectively to a non-expert audience.

  • Hands-on wet lab experience, design of experiments.

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, or protected veteran status and will not be discriminated against on the basis of disability.

For more information on how we support the whole health of our employees throughout their wellness, career and life journey, please visit www.careers.jnj.com (http://www.careers.jnj.com).

Primary Location NA-US-Pennsylvania-Spring House

Other Locations NA-US-Massachusetts-Cambridge, NA-US-California-La Jolla, NA-US-California-San Francisco

Organization Janssen Research & Development, LLC (6084)

Travel Yes, 10 % of the Time

Job Function R&D

Req ID: 2306152908W