[visionlist] Postdoctoral researcher position working with Functional Near-Infrared Spectroscopy (fNIRS)

[Lavie, Nilli]

Functional Near-Infrared Spectroscopy (fNIRS) Researcher at MindVisionLabs (UCL spinout)


MindVisionLabs is a UCL spinout company creating autonomous car technologies through conducting parallel and complementary research in cognitive neuroscience and machine learning. Headed by Prof Nilli Lavie, we are backed by Toyota as both a client and early investor.


We are seeking a cognitive neuroscience/neuroimaging researcher at a postdoctoral level to join us in identifying and measuring markers of attention and visual perception with fNIRS, running experiments using mobile fNIRS in-car, as well as in high-fidelity driving simulators.


The position will be highly collaborative, involving inter-disciplinary research with computer vision/machine learning researchers in the company as well as with members of the Attention and Cognitive Control group at the UCL Institute of Cognitive Neuroscience http://www.attention-focus.com/home. As an early employee you will have the opportunity to shape the research directions of MindVisionLabs and join a generous options scheme.


Salary range between £35,000- £45,000 per annum, pending qualifications and experience.
The position is available from January 1, 2018.


Key Requirements:

Applicants should hold or expect shortly to hold a PhD with a proven record of  research in cognitive neuroscience or related fields, preferably including working with fNIRS.

Applicants should also have excellent quantitative and programming skills in Matlab or Python.

Experience with signal processing, computational modelling, or an interest in machine learning methods would be highly desirable.


To apply:
Please email nilli.lavie at mindvisionlabs.com<mailto:nilli.lavie at mindvisionlabs.com> attaching both a CV and a supplementary personal statement explaining why you would be suitable for this position. The CV should include the name and contacts for two academic references.
Closing date for applications: December 5.



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