Postdoctoral Associate in Auditory System and Computational Neuroscience

Employer
Universiyt of Connecticut
Location
University of Connecticut, Storrs CT
Salary
NIH funded position - follows NIH postdoctoral scale
Closing date
Jan 9, 2023
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Position: The Physiological Acoustics Lab (http://escabilab.uconn.edu) at the University of Connecticut seeks applicants for an interdisciplinary postdoctoral position in systems and computational neuroscience. We are seeking highly motivated and creative applicants that can lead a project on perception and neural coding of speech and vocalizations in the presence of competing natural environmental noises (e.g., restaurant noise, busy street, construction noise etc.). The broad project goal is to study the neural basis for listening in noisy environments and to devise a general computational theory for speech recognition in noise that accounts for both perception and physiology. The project will use a variety of experimental approaches including human perception, awake animal electrophysiology using large scale neural recording arrays, machine learning, and computational modeling.

UConn has a vibrant neuroscience community and there are opportunities for collaboration between departments and institutes. The primary appointment is in Biomedical Engineering, but the work will be conducted in collaboration with the Behavioral Neuroscience division in the Psychology department (Statistical Neuroscience Lab, http://stevenson.lab.uconn.edu; Sensory Perception and Neuroscience Lab, http://read.lab.uconn.edu) as well as Electrical and Computer Engineering and Biomedical Engineering

Qualifications: A PhD in Neuroscience, Biomedical Engineering, Electrical Engineering, Computational Neuroscience, or a related field is required. The ideal candidate will have an interdisciplinary research background in computational and systems neuroscience with prior research experience in awake animal neurophysiology. A strong analytic background in neural data analysis is desirable, particularly modeling neural systems and analyzing datasets from large-scale multi-channel neural recordings. Experience with acoustic signal processing, sound recognition, and machine learning is also desirable.

Appointment: The position is funded through an R01 grant through the Collaborative Research in Computational Neuroscience Program. Salaries follow NIH post-doctoral scale and are based on experience. The initial appointments is for a one year period, with additional years of funding possible upon satisfactory performance.

Apply: Applicants should email Monty Escabi (escabi@engr.uconn.edu) a single PDF file containing a CV that includes past research experience and published work and names of three individuals who can provide reference letters.

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