Scientist I, In Vitro Technologies - Discovery Biotherapeutics
AbbVie
June 26, 2026
On-site
Worcester, MA
$75,000 - $142,500 USD yearly
Clinical Research and Development
Responsibilities:
- Design and execute in vitro display technologies for lead antibody identification and optimization.
- Collaborate to generate stage-gate appropriate in vitro, cellular, and in vivo data packages supporting proof-of-concept (PoC).
- Develop and implement research supporting discovery, optimization, and mechanistic understanding of molecular pharmacology of therapeutic molecules across therapeutic areas.
- Analyze, document, and report data effectively; present results in group settings.
Qualifications:
- BS or MS in Biology (or related field).
- Typically 5+ years of experience (BS) or 2+ years of experience (MS) in a pharmaceutical and/or relevant research environment.
Required Skills & Experience:
- Strong molecular biology skills (e.g., molecular cloning).
- Familiarity with sequence analysis tools (e.g., Geneious, Genedata, PipeBio).
- Experience with biologics, antibodies, antibody fragments, and mimetics.
- Experience with bacterial cell culture.
- Solid understanding of protein structure and function.
- Excellent oral and written communication skills.
- Ability to engage scientific leaders in collaborative research.
- Strong organizational skills; manage multiple projects.
- Team player in a fast-paced, multi-disciplinary environment.
- Ability to adapt to rapid changes in priorities/timelines.
- Proficiency with MS Office Suite (Excel, PowerPoint, Word).
Preferred Skills & Experience:
- Hands-on in vitro antibody discovery display technologies (e.g., phage display, yeast display).
- Binding assay experience (e.g., ELISA, flow cytometry).
- Antibody engineering/optimization (e.g., affinity modulation, liability engineering, humanization).
- Antibody library design and construction.
- Mammalian cell culture.
- Automation of biologics discovery processes.
- Proficiency with Prism, Geneious, Sequencher, and/or Genedata.
- Familiarity with computational approaches; work with AI/ML and Digital Transformation teams to amplify in vitro workflows and contribute to AI/ML infrastructure.
- Design and execute in vitro display technologies for lead antibody identification and optimization.
- Collaborate to generate stage-gate appropriate in vitro, cellular, and in vivo data packages supporting proof-of-concept (PoC).
- Develop and implement research supporting discovery, optimization, and mechanistic understanding of molecular pharmacology of therapeutic molecules across therapeutic areas.
- Analyze, document, and report data effectively; present results in group settings.
Qualifications:
- BS or MS in Biology (or related field).
- Typically 5+ years of experience (BS) or 2+ years of experience (MS) in a pharmaceutical and/or relevant research environment.
Required Skills & Experience:
- Strong molecular biology skills (e.g., molecular cloning).
- Familiarity with sequence analysis tools (e.g., Geneious, Genedata, PipeBio).
- Experience with biologics, antibodies, antibody fragments, and mimetics.
- Experience with bacterial cell culture.
- Solid understanding of protein structure and function.
- Excellent oral and written communication skills.
- Ability to engage scientific leaders in collaborative research.
- Strong organizational skills; manage multiple projects.
- Team player in a fast-paced, multi-disciplinary environment.
- Ability to adapt to rapid changes in priorities/timelines.
- Proficiency with MS Office Suite (Excel, PowerPoint, Word).
Preferred Skills & Experience:
- Hands-on in vitro antibody discovery display technologies (e.g., phage display, yeast display).
- Binding assay experience (e.g., ELISA, flow cytometry).
- Antibody engineering/optimization (e.g., affinity modulation, liability engineering, humanization).
- Antibody library design and construction.
- Mammalian cell culture.
- Automation of biologics discovery processes.
- Proficiency with Prism, Geneious, Sequencher, and/or Genedata.
- Familiarity with computational approaches; work with AI/ML and Digital Transformation teams to amplify in vitro workflows and contribute to AI/ML infrastructure.