[Neuroimaging] Postdoctoral positions available

[Manish Saggar]

[https://tr.cloudmagic.com/h/v6/emailtag/tag/2.0/1539197810/b66430ca7e69eb44a2365b99bb8d8527/2/37dc7c4101057d665b3af19baa29b2ed/91e47bcc09b97ecb510bd665381a6240/9efab2399c7c560b34de477b9aa0a465/newton.gif]
[Apologies for cross-posting]

The Brain Dynamics Lab (http://bdl.stanford.edu) at Stanford is looking to hire 1-2 postdocs with expertise in neuroimaging data analysis to develop/apply computational methods that can quantify transitions in brain activity (or connectivity) in health and disease (specifically, major depression and ADHD).

We use a number of neuroimaging modalities including simultaneous EEG-fMRI and EEG-fNIRS, structural/functional connectivity, and independent fMRI/fNIRS/EEG. We also use computational modeling (e.g., The Virtual Brain) for realistic bio-physical network model simulations and neuromodulation (e.g., TMS) to gain mechanistic understandings for the observed aberrant brain dynamics in patients with psychiatric illness. Other computational tools used in the lab include Topological Data Analysis (TDA) - including Mapper and Persistent Homology - and Deep Learning (DL). Stanford University is located in sunny northern California, deep in the heart of Silicon Valley and a short train ride to San Francisco.

The postdoc will be able to contribute to a number of ongoing research projects in our lab and collaborating labs by analyzing neuroimaging data from those studies. In addition, the postdoc will have the opportunity to develop their own research program with the domain of scientific or methodological problems currently being investigated within the lab (http://bdl.stanford.edu).

The successful candidate should:
• Have a PhD in a relevant field of study and demonstrated experience with the processing and statistical analysis of neuroimaging data.
• Have strong and demonstrated computer programming skills, including Python.  Experience with Nipype is preferred.
• Have strong skills in statistics and machine learning (esp. TDA, DL, etc.)
• Have solid experience with computational data analysis, including strong UNIX/Linux skills and experience using high performance computing clusters.

Our lab is strongly committed to diversity in science, and we particularly welcome applications from members of traditionally underrepresented groups.

Interested candidates should email the following to saggar at stanford.edu:
• A cover letter describing your background and research interests
• CV
• Names and email addresses of two references

The initial position is for one year, with the option to renew for 2-3 years, given satisfactory performance and available funding. The positions are available immediately and applicants will be considered on a rolling basis.


m-

Manish Saggar, Ph.D.
Assistant Professor, Psychiatry
Stanford University
http://bdl.stanford.edu


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