Merge Labs is a frontier research lab with the mission of bridging biological and artificial intelligence to maximize human ability, agency and experience. We’re pursuing this goal by developing fundamentally new approaches to brain-computer interfaces that interact with the brain at high bandwidth, integrate with advanced AI, and are ultimately safe and accessible for anyone to use. About the team: Our In Vivo team sits at the core of Merge Labs’ experimental engine, operating at the intersection of neuroscience, molecular biology, and engineering. We are responsible for executing and enabling in vivo studies across multiple teams, making our role critical to the success of the broader mission. We design, build, and run high-quality, scalable in vivo pipelines, supporting a wide range of experimental needs. As a central function, we collaborate closely with cross-functional partners and serve as the backbone for translating ideas into robust, reproducible in vivo data. Given the breadth of teams relying on our work, we hold ourselves to the highest standards of execution, precision, and reproducibility. We are deeply committed to operational excellence, consistency, and continuous improvement, ensuring that every study is executed with rigor and reliability. About the role: We are seeking a Research Associate with strong in vivo expertise and hands-on surgical experience in rodents to play a critical role in executing and scaling our in vivo operations. This is a highly hands-on position at the core of our experimental work, requiring independence, precision, and the ability to deliver consistent and reproducible high-quality execution across multiple studies. In this role, you will partner closely with Scientists to generate high-quality, reproducible data, continuously optimize workflows, and help build robust, scalable in vivo pipelines from the ground up. Your contributions will be essential to driving execution, enabling rapid iteration, and supporting the advancement of next-generation neurotechnology.
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Job Type
Full-time
Career Level
Mid Level