Postdoctoral Fellowship in Communication Analysis, Modeling, and Intervention in ASD

Title:  Postdoctoral Fellowship in Communication Analysis, Modeling, and Intervention in Autism Spectrum Disorder
Location:  Lexington, Massachusetts, US
Employer:  Lurie Center for Autism, Massachusetts General Hospital
Supervisors/Mentors:  Lisa Nowinski, PhD:  Massachusetts General Hospital, Lurie Center for Autism, Thomas Quatieri, PhD:  MIT Lincoln Laboratory, and Jacob Hooker, PhD: Massachusetts General Hospital, Lurie Center for Autism

Communication Project Overview
The MGH Lurie Center for Autism is seeking a candidate to join a growing and innovative research team in the production, perception and underlying neurobiology of communication in autism spectrum disorder (ASD). One primary research objective is to use advanced signal sensing, neurophysiological mechanistic modeling and analysis technologies to characterize elements of vocal, behavioral, and ‘silent’ (i.e., anticipatory or planned) means of expression and uncover where along the neuro-sensorimotor pathway the challenges of communication lie, from the near fluent to the minimally verbal and nonverbal ASD individual. One key premise is the breakdown of the perceptuomotor link that is essential in the action-perception loop responsible for fluent speech production. This loop can be challenged at different scales of phonetic, syllabic and linguistic sequencing. Characterization will occur synergistically with translation by testing from the clinic to naturalistic environments (home, school, community) in order to achieve large data sets. Here we will use advanced signal enhancement, human/brain-to-machine, and auditory and other sensory feedback technologies to promote the generation of speech or, when speech is not possible, alternative forms of communication. A scientific basis for algorithm development will involve computational and mechanistic models of the speech, language and auditory pathways and their interplay with each other and with fine and gross motor movements, as well as multi-modal data collection and analysis.

The candidate will be involved in richly characterizing the vocal, neural, and behavioral communication strengths and weaknesses in a range of individuals with ASD and rapidly bringing biofeedback technology to naturalistic environments, with the objective to develop translational breakthroughs leading to a first-of-its-kind Communication Technologies Enhancement Center (CTEC) where the individual with ASD can obtain a personalized device and methodology to promote their own communication.

Required Skills

• The candidate should hold a doctorate in Electrical Engineering, Biomedical Engineering, Computer Science, Neural Science, Speech and Hearing Science, or a similar technical field.
• Strong multimodal and neurophysiological signal processing and modeling; speech/hearing bioscience and technology background.
• Demonstrated real-world signal processing, modeling, and machine learning implementations with MATLAB, Python, and/or C++
• Publication record.

• Familiarity with neural science (preferably modeling of neuro-motor and sensory systems) and the neural basis of speech perception and production, vision, and fine- and gross-motor movement.
• Familiarity with neuroimaging, on- and off-body sensing, neural-science-based algorithm development, brain and human computer interfaces, and computational models, as well as data collection and analysis.