Scientist, AAV Engineering

Scientist / Senior Scientist, AAV Engineering
Location: New York City, NY
Department: Gene Therapy R&D

Position Overview:

We are seeking a Scientist or Senior Scientist to join our AAV Engineering team focused on the discovery and development of next-generation AAV capsids for use in gene therapies targeting neurodegenerative and ocular diseases. This individual will contribute to the design, construction, and screening of novel AAV capsid libraries using both rational and directed evolution strategies, and will lead efforts to characterize variant performance across in vitro and in vivo models.

Key Responsibilities:

• Design and generate AAV capsid libraries using rational design and directed evolution approaches.

• Develop and optimize vector assembly workflows to support high-throughput capsid screening.

• Plan and execute in vivo screening campaigns in murine and NHP models; analyze biodistribution and transduction profiles across tissues.

• Establish and refine NGS pipelines for recovery and characterization of AAV variants from tissue samples.

• Develop and implement in vitro screening assays, including binding assays and transduction readouts in relevant cell lines.

• Collaborate with cross-functional teams on vector design, production, and payload optimization.

• Maintain accurate records of experimental design and outcomes; contribute to internal reports, presentations, and publications.

Qualifications:

• Ph.D. in Molecular Biology, Virology, Bioengineering, or a related field, with 0-4+ years of industry or postdoctoral experience; or

• M.S. with 4+ years of hands-on experience in AAV vector engineering.

• Strong foundation in AAV biology, capsid structure-function, and viral vector design.

• Experience with library construction, high-throughput screening, and NGS-based analysis.

• Prior work with in vivo models (murine and/or NHP) for AAV screening preferred.

• Familiarity with CNS and/or ocular delivery is a plus.

• Strong molecular biology and cell culture skills.

• Excellent data analysis and documentation practices.