Senior Scientist, Protein Design

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 Senior Scientist, Protein Design, 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 may be considered on a case-by-case basis.
 

This role presents an exciting 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:

You will work closely with colleagues across the organization to design, develop and deliver on differentiated, best in class therapeutic molecules for a range of clinical indications spanning all therapeutic areas. Qualified candidates will have a strong background in computational biology and a proven track record of seeing designs through experimental testing.

• Work directly with wet-lab scientists and therapeutic areas to design and optimize protein molecules for specific functions and properties, with a focus on antibody therapeutics.
• Collaborate with team members across Therapeutics Discovery on the planning, prioritization, and timely delivery of designs to support multiple concurrent programs
• Serve as an In Silico Discovery Lead on diverse project teams
• Work with ML colleagues to guide development, benchmarking, and application of pioneering generative and discriminative models.
• Model sophisticated biological systems using a variety of methods and tools to advise design methodology.
• Participate in internal and external presentations, peer-reviewed manuscripts and conference proceedings

Qualifications

Education:

• PhD in Biomedical Engineering, Biochemistry, Computational Biology, Computer Science, Structural Biology, Biophysics, Material Science, or other related quantitative field required.

Experience and Skills:

• Advanced experience in computational protein modeling, design, structural biology, and biophysics is required
• Ability to lead projects in cross-functional teams to completion in a collaborative manner is required
• Experience in de novo protein design and sophisticated protein design techniques, such as large scale backbone editing is preferred.
• Experience with antibody and/or nanobody modeling and design is required.
• Experience with high performance computing (on-prem or cloud) is required
• Knowledge of critical wet-lab techniques used in protein engineering such as yeast display, SPR, ITC, CD-spectroscopy is preferred.
• Solid understanding of current machine learning architectures is required.
• Advanced proficiency in Python and related data-science packages such as Pandas and Numpy is required.
• Excellent communication, reporting and team intera