Senior Scientist, Computational Biology

About Alltrna

Flagship Pioneering has conceived of and created companies such as Moderna Therapeutics (NASDAQ: MRNA), Editas Medicine (NASDAQ: EDIT), Omega Therapeutics (NASDAQ: OMGA), Seres Therapeutics (NASDAQ: MCRB), and Indigo Agriculture. Since its launch in 2000, Flagship has applied its unique hypothesis-driven innovation process to originate and foster more than 100 scientific ventures. In 2021, Flagship Pioneering was ranked 12th globally on Fortune’s “Change the World” list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies.

Alltrna is the world’s first tRNA platform company to decipher tRNA biology and pioneer tRNA therapeutics to treat thousands of diseases. Alltrna unlocks tRNA biology to correct disease. The company's platform incorporates AI/ML tools to learn the tRNA language and deliver diverse programmable molecules with broad therapeutic potential. Alltrna has an unprecedented opportunity to advance a single tRNA medicine to unify treatment across a wide range of diseases with the same underlying genetic mutation. Alltrna was founded in 2018 by Flagship Pioneering. For more info, visit www.alltrna.com.

About The Role 

Come join a creative and collaborative team of scientists at Alltrna dedicated to leveraging emerging insights in RNA biology to develop a novel class of human therapeutics. In this role you will apply computational biology methods to turn diverse data streams into scientific insights, which will have a major impact on Alltrna’s tRNA platform.

You will develop computational analyses for Next-Generation Sequencing, proteomics, and high-throughput screening data, and will partner with teams throughout Alltrna to visualize and interpret study results. You will contribute to Alltrna’s computational biology strategy, working in partnership with our Machine Learning, Informatics, Computational Chemistry, and leadership team to address computational technology and infrastructure needs. You will also work closely with other wet- and dry-lab scientists to develop, evaluate, and benchmark performance of new molecular and computational methods. Through these collaborations you will help generate hypotheses and design experiments that drive forward our understanding of tRNA medicines.

Core Responsibilities 

• Contribute to Alltrna’s computational strategy in collaboration with colleagues in Machine Learning, Informatics, Computational Chemistry, and the leadership team
• Develop computational pipelines to analyze NGS data generated using both established and proprietary library preparation methods, whole-cell and targeted proteomics data, and high-throughput screening data
• Perform exploratory analyses on internal and public data to develop new hypotheses for subsequent wet-lab testing
• Formulate and evaluate hypotheses that advance our understanding of tRNA medicines through collaboration with other wet- and dry-lab scientists
• Contribute to improving the software infrastructure underlying analysis pipelines, visualizations, and data apps
• Develop and implement criteria for evaluating experiment integrity and ensuring pipeline and data robustness
• Collaborate with our informatics team to automate analysis pipelines and deploy data apps that promote broader-team access to data and analyses
• Create effective data visualizations and communicate study results to cross-functional teams

Qualifications and Skills

• Ph.D. in computational biology, bioinformatics, or a related field and an additional 5+ years of relevant experience, including 3+ years working with NGS data in an academic or industry setting

• Expert in Python, common data science packages and bioinformatic toolkits
• Experience with computational pipeline development and maintenance (snakemake, nextflow, etc)

• Strong data visualization skills and experience developing data apps (Streamlit/Dash/Flask)
• Experience with computational notebooks (i.e., Jupyter), version control (i.e., Git), code documentation, coding standards, and unit tests
• Excellent communication skills and the ability to clearly explain computational analyses and their implications to team members of diverse backgrounds and drive decision-making

The preferred candidate will ideally also possess the following skills:

• Experience working with proteomics, pooled screening, high-throughput screening, and/or single-cell sequencing data
• Experience working in a cloud computing environment (AWS/GCP)

What We