Postdoctoral and PhD Positions in Computational Neuroscience & Machine Learning at UCLA
Dear All, The Triplett Lab at UCLA is recruiting for multiple postdoctoral and PhD positions in computational neuroscience and machine learning. Projects will span two broad areas: - Statistical machine learning methods for neural data analysis, such as inference of neural circuit connectivity and plasticity rules from large-scale imaging, electrophysiology, circuit perturbation, and behavioral data. - Computational models of cognition, including how neural systems form representations of causal structure and use them for decision-making or planning. Projects will combine neural circuit models and interpretability techniques (e.g. dynamical systems analysis) with behavioral and/or intracranial data to identify and test candidate mechanisms. Postdoctoral applicants should have (or expect to soon receive) a PhD in a quantitative field such as Computational Neuroscience, Applied Mathematics, Computer Science, or a related area. Prospective PhD students must first be admitted to an appropriate UCLA graduate program, such as Neuroscience, Computer Science, or Bioengineering. Interested applicants are encouraged to contact Marcus Triplett ( marcustriplett@ucla.edu) with a CV and brief description of past and future research interests. For more details visit triplett-lab.org. AA/EOE.
participants (1)
-
Marcus Triplett