Principal Scientist, Biophysics & Laboratory Automation

Johnson & Johnson Innovative Medicine•Spring House, PA

3d•Onsite

About The Position

Johnson & Johnson Innovative Medicine is seeking an accomplished Principal Scientist to join Cell Engineering and Analytical Sciences (CEAS), within the Biophysics & Separations team. The role combines deep expertise in protein characterization and separation sciences with the ability to translate scientific workflows into automated, digitally enabled solutions. The scientist will lead biophysics automation efforts in coordination with CEAS automation and data science teams, building on established infrastructure and collaborating with Mass Spectrometry, Cell Line Development (CLD), and Process Development to advance a shared vision for a self-driving laboratory. The position will help create an integrated characterization environment that connects experiments, instruments, data, and analytics. This work is intended to accelerate evaluation of molecules and cell lines, identify product-quality and manufacturing risks earlier, and support more informed scientific decisions as biologics development increases in complexity, speed, and scale. The Principal Scientist will design and implement automated biophysical and protein characterization workflows, perform and interpret characterization experiments, integrate results with CLD information, and use advanced analytics to generate scientific recommendations. The role also includes evaluating emerging analytical, automation, and digital technologies; improving workflow usability and scalability; and providing scientific leadership through mentoring and cross-disciplinary collaboration.

Requirements

Ph.D. in Biophysics, Biochemistry, Analytical Chemistry, Bioengineering, Biotechnology, or a related scientific or engineering discipline.
At least 4 years of demonstrated biopharmaceutical, biotechnology, or related industry experience.
Deep expertise in protein therapeutics characterization and biophysical or separation methods, including relevant experience with CE-SDS, cIEF, SEC-based separations, chromatography, or related techniques.
Ability to independently prepare samples, execute and troubleshoot analytical methods, assess data quality, and interpret results.
Strong understanding of protein quality attributes, including aggregation, fragmentation, charge heterogeneity, and stability, and their implications for molecule and cell-line development.
Ability to design complex experiments, interpret multidimensional datasets, and translate findings into actionable scientific recommendations.
Strong communication, collaboration, and scientific leadership skills, including presenting results and recommendations in team and cross-departmental settings and tailoring technical detail to the audience.
Technical problem-solving aptitude and motivation to take ownership of biophysics automation and data digitalization in partnership with established automation and data science teams.
Willingness and ability to occasionally work outside regular hours to troubleshoot and support ongoing automated experiments.

Nice To Haves

Experience with laboratory automation, including liquid handling, robotics, and integration of analytical instruments with automated sample preparation.
Experience with workflow scheduling and orchestration, including development of high-throughput or unattended analytical workflows.
Scientific programming or scripting, such as Python, for automated data processing, statistical analysis, visualization, and reporting.
Experience with data digitalization and laboratory informatics, including structured capture, standardization, and integration of analytical data across instruments and systems.
Application of AI/ML to scientific data or use of agentic AI tools for programming, analysis, and workflow development.

Responsibilities

Lead the design, development, and implementation of automated workflows for biophysical and protein characterization assays.
Connect sample preparation, instruments, software, and data processing to build practical automated workflows, using scientific programming and agentic AI where applicable.
Automate established platforms such as CE-SDS, cIEF, and SEC-UV, and expand automation to new characterization technologies.
Connect experimental execution with automated data capture, processing, analysis, visualization, and reporting; help establish infrastructure and practices for increasingly autonomous experimentation and scientific decision support.
Design experiments, prepare samples, execute and troubleshoot methods including CE-SDS, cIEF, and SEC-UV, assess data quality, and interpret results.
Characterize product quality, molecular heterogeneity, aggregation, fragmentation, and charge variants to inform molecule and cell-line selection and identify development and manufacturing risks.
Adapt characterization techniques to complex modalities such as bispecific and trispecific antibodies.
Integrate biophysical characterization results with other CLD information and apply advanced analytics, including machine learning and AI-enabled approaches, to identify trends, anomalies, and molecule-specific risks.
Simplify routine biophysics workflows and improve usability to support increased sample volumes and molecular complexity without proportional increases in manual effort.
Evaluate emerging analytical, automation, and digital technologies and partner with digital, data science, and automation teams to advance the self-driving laboratory vision.
Mentor colleagues in biophysical characterization and increasingly automated, data-driven workflows.
Contribute to cross-disciplinary and external collaborations, presentations, publications, and intellectual property.
Occasionally work outside regular hours to troubleshoot and support ongoing automated experiments.