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Computational Biologist - NGS Data Team

Employer
Dyno Therapeutics
Location
Watertown, Massachusetts, US
Salary
Competitive
Closing date
Nov 28, 2022

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Sector
Consultancy/Private Sector
Field
Informatics / GIS
Discipline
Statistics
Salary Type
Salary
Employment Type
Full time
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The Company

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. Dyno was named Startup of the Year in 2020 by Xconomy, Endpoints 11 in 2021, and named one of America's Best Startups in 2022 by Forbes!

The Role

Computational Biologist - NGS Data Team. Next-generation sequencing (NGS) is central to Dyno's high-throughput viral characterization platform, and your work with the NGS Data Team will have a major impact on the future of gene therapy. You will be a translational scientist, combining a deep understanding of biology and data engineering to develop sequencing products in Dyno's data science ecosystem. Specifically, your role will be to develop pipelines to translate raw sequences to meaningful data that can be easily accessed and interpreted by other scientists. In addition to developing methods for processing sequencing data from viral screens, the NGS Data Team collaborates with molecular biologists and engineering teams to design new experiments and approaches to data generation. You will work closely with other teams, including communication of findings, to experimental biologists and machine learning scientists with effective visualization and education to enable decision-making based on the data collected at Dyno.

How You Will Contribute

As a Computational Biologist - NGS Data Team, you will develop methods and build tools to analyze and process next-generation sequencing data, including single cell sequencing data. In this role you will help to develop technology and design experiments to ensure data is interpretable and actionable. This is a highly collaborative position working closely with wet bench scientists and software engineers to enable data based decision making.

Responsibilities

* Develop and refine methods for processing and statistical analysis of next-generation and long-read sequencing data
* Engineer pipelines and data-metadata relationships for emerging technologies, including single-cell gene expression characterization
* Support technology development and contribute to experimental design to ensure data is interpretable and actionable
* Contribute to improving the software infrastructure that supports quantitative data analysis and visualization, including workflow management and dash-boarding

Who You Are

* Team oriented
* Thoughtful & detail oriented
* Committed to rigorous scientific practices
* Appreciate opportunities at the intersections of data engineering and biology

Basic Qualifications

* MS or Ph.D. in bioinformatics, statistics, computer science (or related fields) OR equivalent experience
* 1+ years' experience working with NGS data and single cell sequencing data
* Strong foundation in bioinformatics and data engineering
* Experience developing and maintaining data processing pipelines
* Expertise in Python and relevant data science packages (e.g. pandas, scipy, seaborn)
* Ability to communicate and collaborate with scientists of different backgrounds

Preferred Qualifications

* Internship or work experience in an industry setting
* Publications in peer-reviewed journals or conferences
* Experience with cloud-based platforms (GCP or AWS)
* Familiarity with any of the following: molecular biology, protein engineering, gene therapy, microbial ecology, or virology

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Job Type: Full-time
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