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

Job Function:

Data Analytics & Computational Sciences

Job Sub Function:

Data Science

Job Category:

Scientific/Technology

All Job Posting Locations:

Cambridge, Massachusetts, United States of America, 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 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 and if approved by the Company.

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

• 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 groundbreaking 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 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, disability, protected veteran status or other characteristics protected by federal, state or local law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act.

Johnson and Johnson is committed to providing an interview process that is inclusive of our applicants’ needs. If you are an individual with a disability and would like to request an accommodation, please email the Employee Health Support Center (ra-employeehealthsup@its.jnj.com) or contact AskGS to be directed to your accommodation resource.

The anticipated base pay range for this position is $115,000 to $197,800. 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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