Drs Simon Little and Philip Starr (https://starrlab.ucsf.edu/) are seeking a talented postdoctoral student to study the neurophysiology of movement in Parkinson’s disease using sensing-enabled, deep brain stimulator pacemakers towards automated optimization of adaptive, personalized, brain stimulation.
Drs Little and Starr have pioneered adaptive deep brain stimulation and chronic neural sensing for movement disorders and are now working at the forefront of studies to develop personalized stimulation therapies for patients. This includes research to understand the link between cortico-basal network physiology and fundamental behavior, physiological biomarker discovery and testing of closed-loop stimulation strategies for neurological patients.
They present here an exciting opportunity to work with next generation technology that can continously record and stream intracranial cortical and basal ganglia physiology remotely from patients, in their homes, over multiple days. This will enable longitudinal, remote, high spatio-temporal recordings from patients in the naturalistic environment to investigate the relationship between neural signals and movement. The project will use advanced computer vision technology and motion detection wearbles to track clinical state at home. This will be paired with chronic recordings from the cortex and basal ganglia in patients homes. Control theory and high dimensional search approaches will then be used to optimize adaptive brain stimulation in an automated manner.
This project is supported by a Weill Investigator’s award (https://www.weillneurohub.org/our-programs) and is a collaboration with University of Berkeley (Jack Gallant) and University of Washington (Jeff Heron).
- PhD in Neuroscience, Neuro – engineering or related disciplines.
- Advanced analytical and problem solving skills
- Excellent, leadership, project management and communication skills
- Ability to independently run experiments, analyze data and plan forward strategy combined with excellent team and collaborative working skills
- Highly self-motivated, inquisitive scientist
- Record of publication in peer-reviewed journals
- Experience in neurophysiological analysis and strong analysis skills (Matlab / Python) would be highly beneficial.
- Control systems and machine learning experience.