Postdoc - Theoretical Neuroscience - Helen Wills Neuroscience Institute

Postdoc Theoretical Neuroscience Helen Wills Neuroscience Institute Position overview

Position title:

Postdoc

Salary range:
The UC postdoc salary scales set the minimum pay determined by experience level  the following table(s) for the current salary scale(s) for this position: https://(Use the "Apply for this Job" box below). A reasonable estimate for this position is $69,073 - $77,030.

Percent time: 100%

Anticipated start:
Summer 2026

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

Open date:
February 23, 2026

Next review date:
Tuesday, Mar 10, 2026 at 11:59pm (Pacific Time). Apply by this date to ensure full consideration by the committee.

Final date:
Wednesday, Mar 25, 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 a Postdoc in the Bouchard Lab, in the area of theoretical neuroscience. The Bouchard lab at UC Berkeley is an interdisciplinary team that focuses on understanding how distributed neural circuits give rise to coordinated behaviors and perceptions. Collaboration will be with lab members at Lawrence Berkeley National Laboratory (LBNL).

We are looking for a post‑doctoral researcher 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), in collaboration with 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.

• Designing and executing theory, models, methods
• Application of developed theory, models, methods to neural population dynamic data
• Manuscript preparation
• Presenting research at lab meetings and scientific conferences
• Contributing to grant proposals
• Mentoring students

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

Additional qualifications (required at start)

• PhD (or equivalent international degree) required by the appointment start date.
• No more than three years of post‑degree research experience by start date.

Preferred qualifications

• 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.
• Demonstrated expertise in developing and applying methods for the analysis of neural population data.
• Experience in control theory, information theory, and/or machine learning desirable, required.

Document requirements:

• Curriculum Vitae - Your most recently updated C.V.
• Statement of Research

Reference requirements:

• 3 required (contact information only)

Apply link: /JPF
05295

Help contact: kebouchard

Berkeley, CA

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