This is the person who turns our experiments into results.
Arbor is generating novel datasets. In humans, we image deep brain structures with functional ultrasound, and we will soon be adding ultrasound neuromodulation. Those studies are longitudinal and causal: intervene, image the circuit response, track the symptom, and repeat in the same person over months. In animals, we combine this bidirectional ultrasound with electrophysiological stimulation and recording, giving us causal measurements across a wide range of spatial and temporal scales, in the same subjects over time.
Your primary responsibility is the analysis of those data and the tooling around them, working with a highly quantitative experimental team from the design stage onward. Because these studies will be longitudinal and closed-loop, there will also be a need for optimal experiment design, online analysis implementations, and closed-loop control.
We’re hiring at multiple levels and will calibrate scope and title to your experience: at the earlier end, you’d own the analysis work in close collaboration with the scientific team; with more experience, you’d set the computational direction for the organization.
We’re also still a small, startup-like organization, so everyone fills multiple roles, including hands-on science and the work that gets science done.