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JOB SUMMARY

The Physiological Acoustics Lab at the University of Connecticut seeks applicants for a postdoctoral position in systems and computational neuroscience.

DUTIES AND RESPONSIBILITIES

We are seeking highly motivated and creative applicants who can lead a project on Misophonia, a psychological and behavioral disorder in which individuals experience adverse emotional reactions to specific sounds (“auditory triggers”). The broad project goal is to develop computational models of hearing and perception that are fitted to human perceptual measurements and that can be used to characterize and diagnose misophonia. The models will also be used to develop sound processing tools to remove and de-emphasize auditory triggers (e.g., with headphones) and improve participant outcomes. The project will use a variety of approaches, including human perceptual experiments, machine learning, digital signal processing, and computational models of hearing.

UConn has a vibrant neuroscience community, and there are opportunities for collaboration between departments, institutes, and Universities involved in the project. The primary appointment is in Biomedical Engineering and/or Electrical Engineering. The work will be conducted in collaboration with the Behavioral Neuroscience program in the Psychological Sciences department (Ian Stevenson), the Electrical and Computer Engineering/Biomedical Engineering departments at the University of Connecticut (Monty Escabí), and the Connecticut Institute for Brain and Cognitive Sciences.

MINIMUM QUALIFICATIONS

1. A PhD in Neuroscience, Biomedical Engineering, Computational Neuroscience, or a related field is required.
2. Experience with experimental design, data analysis, and/or modeling.

PREFERRED QUALIFICATIONS

1. Previous experience, education, or general proven knowledge in hearing or speech and language sciences.
2. Interdisciplinary research experience in computational and systems neuroscience with prior research experience in human behavior, animal behavior and/or brain physiology.
3. A strong analytic background, particularly in modeling neural systems and analyzing large datasets.
4. Experience with acoustic signal processing, sound recognition, and machine learning.

APPOINTMENT TERMS

This is a full-time, 12-month position funded through the Misophonia Research Fund on a yearly basis. Other rights and terms and conditions of your appointment are contained in the collective bargaining agreement between the University of Connecticut and the International Union, United Automobile, Aerospace, and Agricultural Implement Workers of America (UAW), Local 6950. 

TERMS AND CONDITIONS OF EMPLOYMENT

Employment of the successful candidate is contingent upon the successful completion of a pre-employment criminal background check.

TO APPLY

Please apply online at Faculty and Staff Positions, Search #499299 to upload a single PDF file containing:

• a resume (including past research experience and published work),
• a one-page statement of prior research experience,
• a one-page statement of future research interests and objectives, and
• the names and contact information of at least two individuals who can provide reference letters. 

All employees are subject to adherence to the State Code of Ethics.

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The University of Connecticut aspires to create a community built on collaboration and belonging and has actively sought to create an inclusive culture within the workforce. The success of the University is dependent on the willingness of our diverse employee and student populations to share their rich perspectives and backgrounds in a respectful manner. This makes it essential for each member of our community to feel secure and welcomed and to thoroughly understand and believe that their ideas are respected by all. We strongly respect each individual employee’s unique experiences and perspectives and encourage all members of the community to do the same. All applicants will receive consideration for employment without regard to race, color, ethnicity, religion, age, sex, marital status, national origin, ancestry, sexual orientation, genetic information, physical or mental disabilities, veteran’s status, status as a victim of domestic violence and/or sexual assault and/or trafficking in persons as defined by Connecticut law, prior conviction of a crime, workplace hazards to the reproductive systems, or gender identity or expression.

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