Assistant Project Scientist Control Theory for Theoretical Neuroscience Helen Wills Neuroscience Institute

Position overview

Position title: Assistant Project Scientist

Salary range: The UC academic salary scales set the minimum pay determined by rank and step at appointment. See the following table for the current salary scale for this position: Table 37 A reasonable full-time estimate for this position is $79,400 to $92,200.

Percent time: 100%

Anticipated start: Summer 2026

Position duration: Initial appointment is for one year with the possibility of renewal based on performance and funding availability.

Application Window

Open date: May 22, 2026

Next review date: Sunday, Jun 7, 2026 at 11:59pm (Pacific Time)

Final date: Wednesday, Jun 24, 2026 at 11:59pm (Pacific Time)

Position description

The Helen Wills Neuroscience Institute at the University of California, Berkeley seeks applications for an Assistant Project Scientist rank in the Bouchard Lab, in the area of control theory for theoretical neuroscience. The Bouchard lab at LBNL/UC Berkeley is an interdisciplinary team that focuses on understanding how distributed neural circuits give rise to coordinated behaviors and perceptions. We are looking for an Assistant Project Scientist to work at the interface of control theory, information theory, dynamical systems, statistical machine learning, and neural time-series data. The goal is to better understand principles and mechanisms underlying distributed brain network computations through the dual lenses of control theory and information theory. This position will focus on developing and applying theory, models, and methods that provide principled understanding of simultaneous multi-region, high-dimensional neural population dynamics from diverse brain areas.

The position is located at UC Berkeley (UCB) and Lawrence Berkeley National Laboratory (LBNL), and is part of a broader collaborative effort between UCSF, LBNL, UCB, and UC Davis.

Qualifications

Basic qualifications (required at time of application)
PhD (or equivalent international degree) or enrolled in a PhD degree program (or equivalent international degree)

Additional qualifications (required at time of start)
Minimum of four years of postdoctoral research experience

Preferred qualifications
Experience in control theory, information theory, and/or machine learning required.
Expertise in theoretical neuroscience preferred
Excellent writing and communication skills
Strong publication record in peer reviewed journals
PhD in neuroscience, computer science, physics, electrical engineering, mechanical engineering, etc.