As a Senior/Principal Scientist of Display and Selection Technologies, you will focus on leading discovery campaigns for novel therapeutic targets that emerge from the company’s internal target ID engine. This role is focused on both display library design and construction (phage, yeast and/or mammalian display platforms) and running affinity-based screens against novel targets at scale, as well as contributing to additional critical functions across a highly matrixed Protein Therapeutics team. The ideal candidate is expected to thrive in a multidisciplinary environment, smoothly collaborate with other Arena BioWorks research teams to explore novel biology, support internal discovery projects and skillfully manage a team.

Specific Responsibilities:

• Independently guide the development and application of antibody discovery campaigns, including the design and execution of display-based screens and selections against novel targets representing new axes of disease biology.
• Develop and optimize new phage, yeast and mammalian display workflows at scale with robust and reproducible pipelines driven by automation.
• Working collaboratively with selection scientists, protein scientists, biochemists, and biologists, you will invent novel screening strategies and assays for challenging targets at the early-stage discovery and downstream development phases of antibody drug discovery.
• Generate data in a timely manner; individually support or lead discovery initiatives; contribute/present at project meetings.
• Oversight of laboratory technicians, research assistants, and fellows participating in projects, including assistance in training, experimental design, and implementation.
• Assume additional responsibilities as needed across the Protein Therapeutics Group.

Qualifications:

• Ph.D. in Biochemistry, Bioengineering, Biophysics, Molecular Biology, or related field, with at least 5–10 years postgraduate experience in an academic or industry setting.
• Demonstrated experience in phage display, yeast display, or similar technologies, with focus on library creation, selection, and analysis. Deep expertise in auxiliary technologies (FACS-based selections and next-generation sequencing) is a plus.
• Experience and/or willingness to integrate in silico methods including immuno-informatics, computational design, and emerging AI/ML methods to accelerate protein engineering at the benchtop.
• Highly adaptable, strong problem solver, with the ability to innovate and a passion for collaboration.
• Strong verbal and written communications skills.
• Highly organized and proficient in documentation, LIMS, and presentation of data.
• Ability to prioritize tasks, set deadlines, and adapt to shifting priorities in response to changing deadlines and needs of the lab.
• Possesses an eager, proactive and collaborative approach to each day; must be a self-starter and persistent in achieving objectives to support our scientific and business goals.