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Principal Scientist, AI-Native Discovery – Large Molecules
Johnson & Johnson. Connect biologics discovery programs with relevant computational capabilities and AI-enabled approaches .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in AI, Machine Learning, and Computational Biology to drive biologics discovery and therapeutic development. Capable of leading cross-functional teams and communicating complex scientific concepts effectively to diverse stakeholders.
Highest-signal resume keywords
PhD In Relevant Scientific DisciplineAI And Machine Learning ExpertiseComputational Biology And Structural ModelingDrug Discovery ExperienceCross-Functional Team Leadership
ATS Keywords
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Hard Skills
Predictive ModelingGenerative ApproachesAgentic AIComputational DesignBiologics Candidate OptimizationData CurationData IntegrationData AnalysisExperimental StrategyTherapeutic Development Processes
Soft Skills
Strong Communication SkillsStakeholder ManagementScientific LeadershipOrganizational Skills
Industry Keywords
Biologics DiscoveryTherapeutic DiscoveryIn Silico DiscoveryAI AdoptionScientific CollaborationInnovative Medicines
About the role
Key responsibilities & impact- Connect biologics discovery programs with relevant computational capabilities and AI-enabled approaches
- Apply AI-enabled computational design, analysis, and decision support in Therapeutic Discovery programs
- Represent In Silico Discovery on cross-functional project teams
- Apply predictive modeling, machine learning, generative approaches, agentic AI, structural modeling, and computational biology to support experimental strategy and biologic candidate design and optimization
- Advance AI-native workflows connecting hypothesis generation, computational design, experimental testing, and model refinement
- Evaluate emerging technologies and contribute recommendations for internal development, acquisition, partnering, licensing, or M&A opportunities
- Champion responsible and scientifically rigorous AI adoption
- Maintain awareness of advances in AI, computational biology, structural modeling, and biologics design
- Contribute to external scientific presence through publications, conference participation, and collaboration with external organizations
- Influence portfolio programs and the evolution of enterprise discovery capabilities
- Contribute to a collaborative global scientific community focused on innovative medicines
Requirements
What you’ll need- PhD in a relevant scientific or technical discipline
- Minimum of 4 years of relevant drug discovery experience, including experience contributing to cross-functional discovery teams
- Knowledge of biologics discovery, candidate optimization, and therapeutic development processes
- Strong scientific leadership, communication, and stakeholder management skills
- Ability to organize and communicate complex data, models, and scientific concepts clearly to partners with diverse technical backgrounds
- Demonstrated expertise in AI, machine learning, agentic AI, structural modeling, computational biology, or computational approaches for antibody design and optimization
- Experience representing a computational function on cross-functional projects
- Experience integrating computational and experimental data to inform program strategy and scientific decisions
- Hands-on experience with large-scale scientific data curation, aggregation, manipulation, integration, mining, and analysis across structured and unstructured data sources
Benefits
Comp & perks- Annual performance bonus eligibility
- Medical insurance
- Dental insurance
- Vision insurance
- Life insurance
- Short- and long-term disability insurance
- Business accident insurance
- Group legal insurance
- Pension plan
- 401(k) savings plan
- Vacation — up to 120 hours per calendar year
- Sick time — up to 40 hours per calendar year
- Holiday pay, including Floating Holidays — up to 13 days per calendar year
- Work, Personal and Family Time — up to 40 hours per calendar year