Research Assistant - Structural Bioinformatics

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Unlike traditional non-profit research organizations, projects supported by Astera operate like high-velocity startups, allowing us to focus on ambitious goals, match structure to problem, and attract strong technical talent and leadership. You can read more about our mission, vision, and programming here.

The diffUSE Project at Astera Institute/Radial is building open infrastructure for dynamic structural biology, making protein conformational and ensemble data findable, validated, and reusable at scale. The Research Assistant will support this mission by maintaining data pipelines, curating structural datasets, and running validation checks across X-ray, cryo-EM, and ensemble-derived data, working closely with Scientists and software engineers on day-to-day technical execution. This is a full-time, in-person role suited to someone early in their research career who wants hands-on exposure to structural biology data infrastructure in a fast-moving, multidisciplinary environment. The ideal candidate is detail-oriented, comfortable with ambiguity, and motivated by the goal of making scientific data more open and reusable.

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  Maintain and run bioinformatic pipelines for structural data processing, curation, and quality control.

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  Support development and benchmarking of validation metrics against experimental datasets.

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  Assist with data deposition, formatting, and documentation to meet community data standards.

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  Help prepare datasets, figures, and summaries for publications, reports, and presentations.

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  Coordinate with Scientists and engineers on routine data management tasks and troubleshooting.

• BS or MS in bioinformatics, structural biology, computational biology, or a related field.

• Working proficiency in Python and familiarity with structural file formats (PDB, mmCIF, mtz).

• Strong organizational skills and close attention to detail in data handling.

• Comfortable working across computational and experimental teams in a research setting.

• Preferred: exposure to crystallography or cryo-EM data processing; familiarity with PDB, EMDB, or related databases.