Postdoc position – Computational neuroscience and machine learning

The Abbasi Lab at the University of California, San Francisco (UCSF) invites applications for three fully-funded postdoctoral positions at the intersection of machine learning and computational neuroscience. This is an opportunity to work on high-impact interdisciplinary problems funded by NIH, Sandler Foundation, and the Weill Neurohub. All projects revolve around adaptation and development of interpretable machine learning tools to systematically analyze large-scale multi-modal data from brain. In particular:

1. In collaboration with the UCSF Multiple Sclerosis (MS) Center, this project aims to systematically integrate and analyze longitudinal MRI and genomics data from hundreds of patients with MS. The project involves the development of state-of-the-art and transparent machine learning tools to build computational pipelines for 3T and 7T MRI.

2. In collaboration with Hongkui Zeng and Bosiljka Tasic at the Allen Institute and Bin Yu at UC Berkeley, this project aims to integrate spatial gene expression and neural data to reveal building blocks of spatial gene expression profiles in the mouse and human brain. These building blocks will partition the brain into completely data-driven 3D brain areas and establish local gene networks. The project involves designing and validating unsupervised and interpretable machine learning frameworks and statistical tools. 

3. In collaboration with the UCSF Neuroscape Center, this project aims to systematically integrate hundreds of different biosensor data collected from the brain and body to predict the emotional state in humans. The data consists of high-density EEG, EMG, ECG, EOG, Continuous blood pressure, Trans Radial Electrical Impedance Velocimetry, respiration, EDA/GSR, and accelerometer readings. This project involves development of interpretable machine learning tools to integrate and analyze large-scale time series data. 

We are looking for highly motivated individuals with a strong computational or neuroscience background (PhD in computer science, computational biology, engineering, computational neuroscience, or related fields) and experience in programming and data analysis. Previous background in computational biology and neuroscience could 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 Neuroscape, 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