The Kirst lab at UCSF and the Bouchard lab at LBNL/UC Berkeley are looking for a joint post-doctoral researcher to work at the interface of dynamical systems, statistical machine learning, and neural time-series data. The goal is to better understand mechanisms underlying flexible network coordination in the brain. This position will focus on developing and applying methods to analyze neurophysiological signals from diverse brain areas.The post-doc will advance the state of the art in analysis methods to characterize brain dynamics and understand distributed computations in diverse brains areas. State-space modeling approaches will be integrated with emerging unsupervised learning and supervised inference procedures. This position will include a strong collaboration with both basic and clinical neuroscience labs across UCSF, UC Berkeley, and LBNL.

The position is located at the University of California, San Francisco (UCSF) and LawrenceBerkeley National Laboratory (LBNL), and is part of a broader collaborative effort between UCSF, LBNL, and UCB. This Bay Area collaboration combines UCSF's strong clinical and experimental neuroscience experience with in vivo cortical electrophysiology, UCB's expertise in theoretical neuroscience, statistical learning and data analysis, and LBNL's supercomputing and applied mathematics together with electronics and microfabrication.Successful applicants will have access to the full range of facilities andexpertise uniquely allowed by this collaboration.

The position has significant flexibility and the lab is committed to the professional development of the members, making it valuable preparation for people who are interested in academic, industrial or entrepreneurial careers. The position has no mandatory teaching or administrative duties, but the successful candidate will take an active role in mentoring students and further developing the research program. Excellent (written and oral) communication skills in English are required. The start date is flexible but ideally would be in June of 2020. Compensation will be commensurate with relevant experience. UCSF has competitive benefits and is an equal opportunity employer. UCSF is located in the Bay Area, which is one of the fastest-growing neurobiology-neurotechnology centers in the United States. The Bay Area offers a wide range of opportunities for recreation, culture, and easy access to domestic and international transportation.

Applicants should have aPh.D. (or equivalent degree) in a computational oriented field (e.g., physics, computer science, electrical engineering, data science, etc.,) and/or a track record of advanced data statistical analysis of neural time-series data. Applicants must be able to work in a collaborative, multi-disciplinary environment and exhibit good communication skills. Experience with scientific programing languages (e.g., C/C++,Python, Matlab) is also required.