Scientist II/Sr. Scientist - Computational Biology

Dyno Therapeutics is reshaping the gene therapy landscape through AI-powered vectors. Through the application of our transformative technologies and strategic partnerships with leaders in gene therapy, we believe a future with life changing gene therapies for millions of people is within reach. 

Our team includes world-class molecular and synthetic biologists, protein engineers and gene therapy scientists working alongside software engineers, data scientists, and machine learning experts to transform the landscape of available gene therapy capsids. Dyno was named Startup of the Year in 2020 by Xconomy, Endpoints 11 in 2021, and one of America’s Best Startups in 2022 & 2023 by Forbes!

The Role

Scientist II/Sr. Scientist - Computational Biology. At Dyno, we are committed to discovering novel AAV capsids that can revolutionize gene therapies. An essential component of the discovery process is capsid validation, wherein AAV capsids identified in high-throughput screening workflows are further characterized using targeted lower throughput multiplexed assays. Computational biology is at the heart of Dyno’s platform. Computational biologists within the Medium Throughput Platform analyze next generation sequencing data from cutting edge biological assays in a statistically rigorous manner. Analysis of these high-resolution validation datasets not only yield insights about high potential capsids but also guide subsequent experiments across multiple workflows and serve as a basis for data-driven decision making.

How You Will Contribute

As a Scientist II/Sr. Scientist - Computational Biology, you will spearhead the development of methods and tools to analyze and process next-generation sequencing data of multiplexed validation studies. You will support quality control (QC) analytics of manufacturing and tissue analysis processes, and contribute to the development of new analyses for process optimization. In this role, you will be instrumental in the development of new methods and the design of experiments to ensure data is interpretable and actionable. You will work in a highly collaborative environment, partnering closely with wet lab scientists to enable data-based decision-making. Staying connected with other Computational Biologists and Software Engineers throughout R&D is a key aspect of this role. Finally, you will see your work directly influence the validation of high-performing capsids that have the potential to have significant clinical impact.

Responsibilities: 

• Analyze next-generation sequencing data collected from bulk and single-cell experiments using rigorous statistical approaches, ensuring high-quality, reliable results.
• Develop and apply quality control analyses to evaluate experimental results, assess the quality of data, and inform critical decision-making processes.
• Partner with wet lab biologists to interpret results, prepare figures, and create presentations for a wide range of audiences across R&D.
• Implement data analysis strategies and relevant statistical methods to test biological hypotheses and support technology development efforts. 
• Develop and refine statistical methods for processing next-generation sequencing data, advancing the capabilities of the team and our technology.
• Use Dyno’s data to identify areas of improvement within the Medium Throughput Platform, driving continuous improvement.
• Collaborate with software engineers to streamline data processing workflows and improve data access, enhancing the efficiency and effectiveness of our operations.

Who You Are 

• A trusted collaborator who can build strong relationships with team members
• Intrinsically motivated to solve complex problems, with a drive to deliver solutions
• A team player who understands the importance of collective success
• Detail-oriented, with a thoughtful approach to tasks and challenges
• Excited about the intersection of data science and biology, and its potential to transform lives

Basic Qualifications

• Ph.D. in computational biology, statistics, physics (or related fields) or equivalent industry experience
• 2+ years of experience working in a post-graduate academic or industrial setting
• Proficiency in Python and associated data science packages (e.g. pandas, seaborn, matplotlib, sqlalchemy)
• Demonstrated experience drawing conclusions from data analysis of NGS-based or other large scale biological datasets
• Demonstrated experience in working with scientists of different backgrounds
• Proficiency in statistics

Preferred Qualifications

• Work experience in an industry setting
• Publications in peer-reviewed journals or presentations at conferences
• Proficiency in bioinformatics pipeline development
• Familiarity with molecular biology or protein engineering
• Hands-on experience in a wet lab setting is a plus