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

About the role

The Helen Wills Neuroscience Institute at the University of California, Berkeley seeks applications for an Assistant Project Scientist rank in the Bouchard Lab, focusing on control theory, information theory, dynamical systems, statistical machine learning, and neural time-series data.

Responsibilities

• Develop and apply theory, models, and methods to understand distributed brain network computations from diverse brain areas.
• Work at the intersection of control theory, information theory, dynamical systems, statistical machine learning, and neural time-series data.
• Collaborate with experts from UCSF, LBNL, UCB, and UC Davis to leverage unique facilities and expertise.

Requirements

• 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 preferred.

Qualifications

• Excellent writing and communication skills.
• Strong publication record in peer-reviewed journals.
• PhD in neuroscience, computer science, physics, electrical engineering, mechanical engineering, etc.

Skills

Not specified.

Benefits

Not specified.

Pay

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.

Schedule

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