[visionlist] Postdoctoral positions investigating human decision-making 'in-the-wild’ at Columbia University

Paul Sajda ps629 at columbia.edu
Tue May 21 12:11:53 -04 2019

Postdoctoral positions investigating human decision-making ‘in-the-wild’ at Columbia University

The Laboratory for Intelligent Imaging and Neural Computing (LIINC) (liinc.bme.columbia.edu <http://liinc.bme.columbia.edu/>) at Columbia University has openings for two postdoctoral positions.  We are conducting a major study investigating human decision-making in complex environments. Specficially we are using perturbation-based multimodal imaging to identify neural correlates of decision-making processes that we can identify in both laboratory conditions and “in the wild”.  As a member of this team you will work on a multidisciplinary project focused on developing testable models of human brain dynamics that govern rapid decision-making in natural environments.  The project will also use machine learning, particularly deep learning, to make linkages between EEG and fMRI neuroimaging measurements and tasks that are carried out in both highly controlled laboratory environments and those that are acquired in less well-controlled, but more ecologically realistic virtual (VR) and augmented reality (AR).  The project will develop and build upon a computational framework that enables fusion and  “transcoding” of neural and physiological measurements between different modalities and noise conditions, enabling development of a macro-scale neural circuit model that is based on high resolution neuroimaging data as well as real-world tasks and behavior. In later years, the project will also use closed-loop, endogenously triggered, neuromodulation to test causal interactions in this circuit and how these relate to behavior. Background/experience in one, or preferable several, of the areas below is required:

1. Simultaneous EEG/fMRI experiments
2. EEG-TMS or fMRI-TMS experiments
3. Mobile EEG + physio measurements (EDA, eye-tracking, pupillometry, HR etc).
4. Design of complex decision-making experiments in virtual reality 
5. Experience in transfer learning and/or multimodal learning.
6. Computational models of decision-making

The positions are for 3 years (renewable annually pending satisfactory performance and availability of funds). 

Applicants must have a Ph.D. in Biomedical Engineering, Computer Science, Electrical Engineering, Cognitive Neuroscience, or a related fields and should possess strong analytical programming skills (e.g., Python). Starting date is flexible, preferably September 2019 to December 2019.

LIINC is directed by Paul Sajda (liinc.bme.columbia.edu/author/paulsajda/ <http://liinc.bme.columbia.edu/author/paulsajda/>) and is a laboratory within the Department of Biomedical Engineering.  It is  also part the Columbia Data Science Institute as well as an affiliate of the Zuckerman Institute for Mind, Brain and Behavior. 

To apply for a position, please send your CV, a brief statement of research interests, and contact information for three references to Paul Sajda (psajda at columbia.edu <http://psajda@columbia.edu/>).

Paul Sajda, Ph.D.
Departments of Biomedical Engineering,
Electrical Engineering and Radiology 
Member, Data Science Institute
Columbia University
Mail: 351 Engineering Terrace Building, Mail Code 8904
	1210 Amsterdam Avenue
	New York, NY 10027
Office: 1010 NWC Building
	    Corner of 120th and Broadway
tel: (212) 854-5279
fax: (212) 854-8725
email: ps629 at columbia.edu

Chair, IEEE BRAIN Initiative

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