Senior Scientist, In Silico Discovery

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

Job Function: Discovery & Pre-Clinical/Clinical Development

Job Sub Function: Chemical Research

Job Category: Scientific/Technology

All Job Posting Locations: Beerse, Antwerp, Belgium, La Jolla, California, United States of America, Spring House, Pennsylvania, United States of America

Job Description: Senior Scientist, In Silico Discovery, J&J IM

At Johnson & Johnson,we believe health is everything. Our strength in healthcare innovation empowers us to build aworld where complex diseases are prevented, treated, and cured,where treatments are smarter and less invasive, andsolutions 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. We have two positions for talented computational Senior Scientists in CADD technology development, joining our cutting-edge In Silico Discovery department within Therapeutics Discovery at J&J. The CADD technology development group is focused on increasing the impact of advanced physics- and structure-based methods, including MD, FEP, and co-folding, across the portfolio, with particular emphasis on sophisticated workflows and automation efforts. Belgium is the primary location but California and Pennsylvania will be considered. The positions involve developing computational methods and workflows in structure-based drug design, physics-based modeling, and co-folding to advance our early drug discovery portfolio. A particular focus will be structure-based automation within autonomous design-make-test-analyse (DMTA) cycles. The two scientists will play a major role in building structure-based components and workflows for this automated environment. Candidates should understand the computational chemistry steps and tools used in structure-based discovery and have strong coding and development skills to accelerate our efforts in this area. A key objective will be to advance the core automated functionality from its current prototype stage to full portfolio deployment over the coming years. The scientists will work closely with colleagues in IT, ISD Cheminformatics, and platform teams to develop robust solutions. Knowledge of software product development for computational drug discovery would be beneficial. In addition to delivering a functioning automated structure-based workflow to tight timelines, the roles will involve expanding the scope of automation by increasing the proportion of chemistry that can successfully pass through existing tools and by identifying and incorporating new tools into automated workflows. The group will also increase the role of co-folding in automation, and experience in this area would be beneficial.

Responsibilities:

• Develop components for automated structure-based modeling workflows, such as ligand preparation, protein preparation, docking, docking selection, and free energy calculations, and advance them from prototypes to deployable solutions.
• Work with colleagues to expand the scope of existing automated components and develop automation for new structure-based tools.
• Collaborate with platform and automation teams to implement scientific workflows using common architectures, reusable services, and enterprise standards.
• Contribute requirements, user feedback, and future workflow needs to shape the evolution of our workflow platform and automated DMTA environment.
• Ensure scientific workflows align with platform strategy, technical standards, security requirements, and operational best practices.
• Work with colleagues to explore and develop the use of co-folding across computational workflows, including future automation efforts.
• Leverage agentic AI to support programming, accelerate development, and expand AI-enabled workflows.
• Work collaboratively across In Silico Discovery with our global CADD, Drug Discovery Data Sciences, Cheminformatics, and In Silico Biologics teams.

Required skills:

• A PhD in computational science, computational chemistry, or a related field.
• Knowledge of structure-based computational drug discovery.
• Strong programming skills, preferably in Python.
• Experience developing automated workflows, pipelines, or scientific applications.
• Familiarity with workflow orchestrat