Post-Doc Position for Neuroscience in the Everyday World
The BOAS Lab is offering a full time PostDoc position in the area of applied biosignal processing applied to functional neuroimaging in the everyday world at the Boston Universities (BU) Neurophotonics Center. COVID-19 emergency response permitting, it is hoped that this position will start before the end of 2020, but start delays can be accommodated. BU’s Biomedical Engineering Department is among the top tier biomedical engineering departments in the US and in a close network with other leading research institutions within the greater Boston area such as Massachusetts General Hospital, Harvard and MIT.
The position is with David Boas, director of the Neurophotonics Center. The grant for this position is expected to be funded in the summer of 2020 and will run 5 years.
Our vision is to build a portable, miniaturized, lightweight, high-density wearable combined – functional Near Infrared-Spectroscopy (fNIRS) – Electro-Encepholography (EEG) – Eye-tracking system for enabling “Neuroscience of the Everyday World” by permitting long duration continuous monitoring of normal / altered brain activity during movement, perception, and social interaction in real time and in the real world.
The work in the offered position will address two major challenges in the analysis of the multimodal signals:
- Brain imaging signal components must be reliably separated into evoked brain activity, local and systemic physiological interference and non-physiological noise, to reject artifacts from movement/interaction and the environment. This challenge will be tackled by building on top of our latest developed methods that incorporate state-of-the-art multivariate Machine Learning.
- The Everyday World yields a plethora of sensory stimuli that generate the context for linking brain activity and behavior. The goal will be to automatically generate context from the audio, video, and eye-tracking data using available cutting edge computer vision / text to speech solutions; leading towards automatic, continuous and probabilistic data labeling that enables segmentation of the EEG-fNIRS signals using keyword / context search.
If you would like to apply, please contact David Boas at Boston University.