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Principal Scientist, Generative Deep Learning - 2406206852W

Description

Johnson & Johnson Innovative Medicine is currently seeking a Principal Scientist, Generative Deep Learning to join our In Silico Proteins team within the Therapeutics Discovery organization, with a preference for this individual to be located at one of our sites in Spring House, PA, or Cambridge, MA. Remote work options in the US may be considered on a case-by-case basis.

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 https://www.jnj.com/.

For more than 130 years, diversity, equity & inclusion (DEI) has been a part of our cultural fabric at Johnson & Johnson and woven into how we do business every day. Rooted in Our Credo, the values of DEI fuel our pursuit to create a healthier, more equitable world. Our diverse workforce and culture of belonging accelerate innovation to solve the world’s most pressing healthcare challenges.

We know that the success of our business – and our ability to deliver meaningful solutions – depends on how well we understand and meet the diverse needs of the communities we serve. Which is why we foster a culture of inclusion and belonging where all perspectives, abilities and experiences are valued and our people can reach their potential.

At Johnson & Johnson, we all belong.

This role presents a great opportunity to spearhead our molecular design and simulation initiatives, supporting and accelerating our drug discovery and development pipeline of protein-based therapeutics while collaborating with a passionate team of scientists and engineers. Your work will be pivotal in building, evaluating, refining, and applying sophisticated computational approaches and infrastructures. Your efforts will drive the discovery of complex molecules and expedite the development of protein therapeutics across various modalities and indications.

Key Responsibilities:

In this pivotal role, you will collaborate extensively with interdisciplinary teams across the organization to develop and refine deep learning methodologies to support the design of ground breaking therapeutic molecules for a broad spectrum of clinical indications across all therapeutic areas and protein-based modalities. The preferred candidate will have an extensive background in deep learning and a desire to apply this knowledge to protein design.

• Lead the development, refinement, and fine-tuning of generative models, such as RFDiffusion, ProteinMPNN, and EvoDiff to enhance our capabilities in protein design.

• Implement new structure-based protein design methods using the latest advancements in AI - including diffusion, flow-matching, Graph Neural Networks (GNNs), Variational Autoencoders (VAEs), and other deep learning architectures.

• Integrate Multi-Property Optimization techniques into various generative methods to improve the efficacy and specificity of target molecules.

• Employ contrastive learning techniques to improve model adaptability and performance, particularly in differentiating functional protein structures.

• Collaborate with multi-functional teams to translate sophisticated scientific challenges into actionable strategies and ensure the alignment of AI tools with scientific goals.

• Maintain up-to-date knowledge of the latest trends in AI/ML, particularly in generative and discriminative modeling techniques, evaluating their potential impact on our research and development efforts.

• Work with external innovation partners to collaborate on pioneering developments in generative protein design.

Qualifications

• • A PhD with 2 years of experience in Computer Science, Data Science, Computational Biology, Bioinformatics or a related field, with a strong emphasis on machine learning is required.

• Validated expertise in the development and application of generative AI models, including deep learning architectures and techniques such as diffusion, VAEs, contrastive learning, GNNs, and Large Language Models (LLMs) is required.

• Proficient in scientific programming and software development, with expertise in Python or C and deep learning frameworks such as TensorFlow or PyTorch is required.

• Experience with high performance computing and cloud-based compute solutions such as AWS is preferred.

• Experience in applying ML methods to computational protein design or modeling is preferred.

• Outstanding communication and leadership skills, capable of leading innovative projects and encouraging a team towards ground breaking solutions is required.

• Familiarity with large datasets, understanding of data analysis workflows, and/or knowledge of querying languages such as SQL is preferred.

• Experience with powerful ML packages for protein modeling and design such as AlphaFold, RosettaFold, ESMFold, ProteinMPNN, RFDiffusion, Chroma, IgFold, EvoDiff, etc is preferred.

• Desire for continuous learning and the ability to identify, evaluate and deploy emerging algorithms, models, and ML architectures is required.

• Up to approximately 10% travel may be required.

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. The anticipated base pay range for this position is $113,000 to $195,500. The Company maintains highly competitive, performance-based compensation programs. Under current guidelines, this position is eligible for an annual performance bonus in accordance with the terms of the applicable plan. The annual performance bonus is a cash bonus intended to provide an incentive to achieve annual targeted results by rewarding for individual and the corporation’s performance over a calendar/performance year. Bonuses are awarded at the Company’s discretion on an individual basis. Employees and/or eligible dependents may be eligible to participate in the following Company sponsored employee benefit programs: medical, dental, vision, life insurance, short- and long-term disability, business accident insurance, and group legal insurance. Employees may be eligible to participate in the Company’s consolidated retirement plan (pension) and savings plan (401(k)).

Employees are eligible for the following time off benefits:

Vacation – up to 120 hours per calendar year

Sick time - up to 40 hours per calendar year; for employees who reside in the State of Washington – up to 56 hours per calendar year

Holiday pay, including Floating Holidays – up to 13 days per calendar year of Work, Personal and Family Time - up to 40 hours per calendar year

Additional information can be found through the link below. https://www.careers.jnj.com/employee-benefits

The compensation and benefits information set forth in this posting applies to candidates hired in the United States. Candidates hired outside the United States will be eligible for compensation and benefits in accordance with their local market.

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Primary Location NA-US-Pennsylvania-Spring House

Other Locations NA-US-Massachusetts-Cambridge, NA-US-Pennsylvania-Spring House, NA-United States

Organization Janssen Research & Development, LLC (6084)

Job Function Data Science

Req ID: 2406206852W