Assistant Project Scientist - Control Theory Theoretical Neuroscience - Helen Wills Neurosc

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. 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.

Open date:
May 22, 2026

Next review date:
Saturday, Aug 8, 2026 at 11:59pm (Pacific Time). Apply by this date to ensure full consideration by the committee.

Final date:
Tuesday, Sep 8, 2026 at 11:59pm (Pacific Time). Applications will continue to be accepted until this date, but those received after the review date will only be considered if the position has not yet been filled.

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. This Bay Area collaboration combines UCSF/UCD's strong clinical and experimental neuroscience experience with in vivo cortical electrophysiology, UCB's expertise in theoretical neuroscience, statistical learning and data analysis, LBNL's supercomputing and applied mathematics, together with electronics and micro‑fabrication.

Successful applicants will have access to the full range of facilities and expertise uniquely allowed by this collaboration.

PhD (or equivalent international degree) or enrolled in a PhD degree program (or equivalent international degree).

Minimum of four years of postdoctoral research experience.

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

• Curriculum Vitae – Your most recently updated C.V.
• Cover Letter
• Research Statement – discuss research accomplishments and proposed plans. This can include, for example, your publication record, awards, presentations, inclusive research practices that promote the excellence of your research, and areas for future research. (Optional)

• 3 required (contact information only)

(Use the "Apply for this Job" box below)./JPF
05380

kebouchard

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