Postdoc position – Machine learning, computational and clinical neuroscience

The lab of Reza Abbasi-Asl at the University of California, San Francisco (UCSF) invites applications for a fully-funded postdoctoral position at the intersection of machine learning, computational and clinical neuroscience. The project seeks to develop quantitative methods to analyse multi-modal data from patients with neurological disease. The data includes one-of-a-kind measurements of MRI, genetic variants, electronic health record, etc from thousands of patients. The role of the candidate is to develop analysis and modeling frameworks to identify scientifically meaningful patterns in patient data that are associated with the disease processes. The project involves predictive modeling, biomedical image and signal processing, interpretation inference, artificial neural networks, visualization, etc. This is an opportunity to work on a highly impactful real-world problem within an interdisciplinary and collaborative environment.

We are looking for highly-motivated individuals with a strong quantitative background (PhD in computer science, engineering, computational neuroscience, mathematics, or related fields) and experienced in programming and data analysis. Previous background in neuroscience or imaging would be highly beneficial.

UCSF is part of the 10-campus University of California, the world’s premier public research university system, and the only of its campuses dedicated to graduate and professional education. UCSF Neurology has been consistently ranked among the top departments of neurology at US medical schools. The successful candidate will benefit from various clinical and basic science resources at UCSF including extensive learning and research support. As a part of the Weill Institute for Neuroscience, our laboratory is located on the Mission Bay campus providing access to the UCSF Neuroscience and Bioengineering communities including the Kavli Institute for Fundamental Neuroscience and Baker Computational Health Science Institute.

Additional information is available at: ​

Candidates should send their CV, research statement, expected date of availability, and the contact information for three references to