Our lab will be moving to Washington University in St. Louis in July 2021. We are looking for two highly motivated postdoctoral scholars to work on NSF and DoD funded projects. One postdoctoral scholar will use human single-neuron recordings to study the neural circuits underlying social attention, and the other postdoctoral scholar will use multimodal neuroimaging techniques to study social behavior and brain networks in people with autism. The research will be conducted in a highly collaborative environment using state-of-the-art equipment, facilities, and analytical methods. The postdoctoral scholars will collaborate with an established team of investigators within and outside WashU and have ample opportunity to learn new techniques and methods.
- Applicants must hold a Ph.D. in systems, cognitive, or computational neuroscience, or in physics, electrical engineering, or computer science, with relevant research expertise in neuroscience.
- Applicants must also have strong programming (Matlab or similar) skills.
- Individuals with previous human intracranial EEG expertise and/or macaque single-neuron recordings that wish to expand into human single-unit recordings are encouraged to apply.
Our lab combines multimodal and advanced measurement techniques with sophisticated computational approaches to understand the neural mechanisms and neural computations underlying social attention, face processing, emotion, memory, and decision making. Overarching questions involve how the brain figures out what is important in the environment, how socially relevant stimuli pop out and attract attention, how faces are processed and represented in general, and how memory is modulated by attention. We are particularly interested in the neural computations underlying these cognitive processes: multimodal approaches allow us to investigate these questions from the microscopic single-neuron and neural circuit level using our state-of-the-art human single-neuron recordings as well as macroscopic level using fMRI, EEG, and intracranial EEG (sEEG and ECoG). These multimodal experimental approaches are powered by sophisticated computational approaches that can deal with complex and large datasets.