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recruiting lifecycle, from sourcing passive candidates through offer stage. This includes building pipelines in channels most recruiters overlook, conducting initial screens, and carrying searches through
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opportunities reach the scientists, students, educators, and grantees who rely on them, as well as the general public. That work runs across web, email, social, paid media, and in-person channels. The team is
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. For the next six months, this role will work across the full recruiting lifecycle, from sourcing passive candidates through offer stage. This includes building pipelines in channels most recruiters overlook
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of network connectivity, synapses, and ion channels. The team currently focuses on the neural basis of navigation behavior in Drosophila , combining electrophysiology and optical physiology in behaving
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. These tools write and execute code, optimize experimental and model parameters, and drive instruments. Letting AI agents act on shared research infrastructure requires serious safety engineering. The
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for high-throughput screening; viral vector production; NGS library preparation; and/or basic coding skills for data analysis including R or Python. Dynamic, adaptable, and comfortable working in a fast
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business problem, selecting the right approach, writing the code, and operating what gets built. The work is technical, consequential, and visible across the organization. What you will actually do Build
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recording hardware, behavioral rigs, electronics, 3D-printed parts, and analysis code] and who wants direct exposure to modern systems neuroscience rather than a narrowly defined coding or bench-only position
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code and brings a critical eye to interpreting results within their research context. As you grow in the role, you'll gain increasing independence, while knowing when to loop in the computational lead or
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for microscopy image analysis are especially relevant. Include a link to a code repository if possible. If you contributed to a joint project, please describe your specific contributions. Briefly