Senior Scientist, Biologics Design and Display, Discovery Biologics
Merck
June 30, 2026
On-site
Boston, MA
Clinical Research and Development
Senior Scientist, Biologics Design and Display, Discovery Biologics
Responsibilities:
- Design and execute in vitro display campaigns for hit discovery and lead optimization to support discovery and development of therapeutic candidates
- Generate and leverage experimental and NGS data to develop machine learning models that enhance predictive performance and accelerate biologics lead optimization and engineering
- Support display workflows (data analysis, structure analysis, library designs, and sequence nomination) using AI/ML and other computational tools
- Stay current with external scientific/technological advancements and continuously drive innovation in display platform capabilities
- Collaborate across multiple functional areas to advance therapeutic candidates
- Communicate experimental results in project and team meetings
Qualifications & Experience:
- PhD in Biochemistry, Bioengineering, Computational Biology, Molecular Biology, Biotechnology, Protein Engineering, Chemical Biology or related STEM discipline with 0–3 years; MS with >3 years; or BS with >6 years post-grad industry/academic experience
- Expertise in antibody discovery and optimization using in vitro display technologies
- Expertise applying AI/ML or computational structure analysis tools in antibody discovery and optimization
- Strong analytical and problem-solving skills
- Excellent communication and organizational skills
Required Skills:
- Hands-on expertise in at least one molecular display technology (phage, yeast, or mammalian)
- Knowledge of NGS technology including NGS data generation and analysis
- Ability to build and use computational tools for therapeutic discovery and optimization
- Familiarity with lead optimization strategies and display library design methodologies
- Proven ability to work in a multi-disciplinary collaborative team
Preferred Skills:
- Hands-on expertise designing, building, and screening lead optimization libraries
- Experience with computational structural analysis tools
- Experience with laboratory automation platforms for high-throughput workflows
Application:
- Apply via https://jobs.merck.com/us/en (or Workday Jobs Hub for current employees). Requisition ID: R405124.
Responsibilities:
- Design and execute in vitro display campaigns for hit discovery and lead optimization to support discovery and development of therapeutic candidates
- Generate and leverage experimental and NGS data to develop machine learning models that enhance predictive performance and accelerate biologics lead optimization and engineering
- Support display workflows (data analysis, structure analysis, library designs, and sequence nomination) using AI/ML and other computational tools
- Stay current with external scientific/technological advancements and continuously drive innovation in display platform capabilities
- Collaborate across multiple functional areas to advance therapeutic candidates
- Communicate experimental results in project and team meetings
Qualifications & Experience:
- PhD in Biochemistry, Bioengineering, Computational Biology, Molecular Biology, Biotechnology, Protein Engineering, Chemical Biology or related STEM discipline with 0–3 years; MS with >3 years; or BS with >6 years post-grad industry/academic experience
- Expertise in antibody discovery and optimization using in vitro display technologies
- Expertise applying AI/ML or computational structure analysis tools in antibody discovery and optimization
- Strong analytical and problem-solving skills
- Excellent communication and organizational skills
Required Skills:
- Hands-on expertise in at least one molecular display technology (phage, yeast, or mammalian)
- Knowledge of NGS technology including NGS data generation and analysis
- Ability to build and use computational tools for therapeutic discovery and optimization
- Familiarity with lead optimization strategies and display library design methodologies
- Proven ability to work in a multi-disciplinary collaborative team
Preferred Skills:
- Hands-on expertise designing, building, and screening lead optimization libraries
- Experience with computational structural analysis tools
- Experience with laboratory automation platforms for high-throughput workflows
Application:
- Apply via https://jobs.merck.com/us/en (or Workday Jobs Hub for current employees). Requisition ID: R405124.