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    Recursion · United States

    rollingRemotePaidPosted 2026-05-28
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    About the role#

    Recursion is maintaining an Internship Talent Network to identify potential candidates for future openings. This is a paid, full-time opportunity for individuals interested in contributing to the intersection of biotechnology and artificial intelligence. We welcome students and graduates from fields including Biology, Biomedical Engineering, Pharmaceutical Sciences, Computer Science, Data Science, Chemistry, Psychology, and Human Resources.

    What you'll do#

    • Engage in projects focused on the integration of biology and AI.
    • Collaborate with cross-functional teams to learn industry practices.
    • Contribute to discussions regarding ethical practices in scientific research.
    • Support company values through daily contributions and team collaboration.
    • Participate in ongoing learning and professional development initiatives.

    What you'll need#

    • A strong passion for improving lives through science.
    • Ability to work effectively as part of a diverse team.
    • Strong communication skills and the initiative to collaborate across functions.
    • Adaptability and an eagerness to learn in a changing environment.

    Location & details#

    • Work Modality: Remote
    • Location: United States
    • Term: Rolling
    Relevant fields:BiologyBiomedical EngineeringPharmaceutical SciencesComputer ScienceData ScienceChemistryPsychologyHuman Resources

    About Recursion

    Founded in 2013, Recursion is a public biotechnology research company that utilizes a proprietary platform to decode biological and chemical information for drug discovery. The organization employs between 501 and 1,000 people and focuses on areas including oncology, neuroscience, and rare diseases. Headquartered in Salt Lake City, the company maintains additional locations in New York, London, Montréal, and the Oxford area. Its operations integrate large-scale wet lab experimentation with machine learning and supercomputing to analyze biological relationships.

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