The lab integrates systems, behavioral, cellular, and computational approaches to build a deeper understanding of the principles governing learning.
- How are behavioral errors and other events (e.g., predictions) that control learning computed and encoded?
- Are the rules for plasticity specialized to support specific learning tasks?
- How do the local rules implemented at synapses throughout a circuit together define an effective algorithm for tuning that circuit’s performance?
- How does meta-plasticity support learning and meta-learning?
We are seeking a motivated postdoc to join us in these exciting scientific efforts.
Candidates should have a PhD in systems neuroscience or related discipline. Preference will be given to candidates with in vivo electrophysiology experience. Lab members are encouraged to learn new techniques as needed to advance their projects.
The PI, Jennifer Raymond, is committed to providing the strong mentorship and support needed for postdocs to achieve their scientific and professional goals; the lab provides a highly collegial scientific environment; and the broader Stanford community provides unsurpassed opportunities for collaboration and professional development.
Salary starting at $73,000/year plus benefits, commensurate with experience.
Interested individuals should send a brief cover letter describing experience and goals, a CV, and the names and contact information for three references to Jennifer Raymond: je...@stanford.edu