Wednesday, March 27, 2019

Postdoc Positions in Cognitive Neuroscience of Communication at the University of Connecticut

The Cognitive Neuroscience of Communication-CT program is funded by a T32 Institutional Research Service Award from the NIH (Inge-Marie Eigsti & Emily Myers, Program Directors). The goal of this program is to provide targeted training in the cognitive neuroscience of communication disorders to predoctoral and postdoctoral scholars.  We invite applications for two-year postdoctoral fellowships, to begin in the Fall of 2019.
Postdoctoral trainees will work under the supervision of one or more mentors on the CNC-CT team. These mentors are: Richard Aslin (Haskins Labs and University of Connecticut), Inge-Marie Eigsti, Deborah Fein, Roeland Hancock, Fumiko Hoeft, Nicole Landi, James Magnuson, Jay Rueckl (Psychological Sciences, University of Connecticut), and Emily Myers, Erika Skoe, and Rachel Theodore (Speech, Language, and Hearing Sciences, University of Connecticut).  For more information about the details of the training program, visit the program’s website (  Note that applicants must be US citizens or green card holders.
The successful candidate will join the intellectually rich community at the University of Connecticut, and will have opportunities to collaborate with an outstanding group of scientists and clinicians and to build an independent research program.
  1. PhD in a relevant field, such as Psychology, Cognitive Neuroscience, or Speech, Language, and Hearing Sciences.
  2. Evidence of research productivity.
  3. Applicants must contact a prospective mentor from the team to assess degree of fit to the program.
  1. Experience with neuroimaging and neuromodulation methods, (e.g. ERP/EEG, MEG, fMRI, fNIRS, tDCS, TMS).
  2. Experience with clinical populations affected by communication disorders (e.g. aphasia, developmental language disorder, reading disorder, hearing loss, autism).
  3. Computational skills including advanced statistical methods, coding abilities (e.g. R, Python), or computational modeling experience.
This will be a full-time, 12-month, two-year appointment based on funding availability, performance, and mutual agreement.  Salary will be commensurate with experience and consistent with NIH NRSA stipends. We anticipate a Fall 2019 start date. For additional information regarding benefits visit:  
To apply, first contact a prospective mentor from the mentorship team. If that person agrees to sponsor your application, you will work with your prospective mentor to develop a one-page research proposal detailing your planned research and training during the traineeship. Next, please apply online at, Staff Positions, Search #2019433. Submit a letter of interest including the one-page research proposal, a curriculum vitae, up to three representative publications, and the contact information for three references. Questions regarding this position may be directed to Directors Eigsti or Myers at
Employment of the successful candidate will be contingent upon the successful completion of a pre-employment criminal background check. (Search # 2019433)
This job posting is scheduled to be removed at 11:59 p.m. Eastern time on May 1, 2019.
All employees are subject to adherence to the State Code of Ethics, which may be found at

The University of Connecticut is committed to building and supporting a multicultural and diverse community of students, faculty and staff. The diversity of students, faculty and staff continues to increase, as does the number of honors students, valedictorians and salutatorians who consistently make UConn their top choice. More than 100 research centers and institutes serve the University’s teaching, research, diversity, and outreach missions, leading to UConn’s ranking as one of the nation’s top research universities. UConn’s faculty and staff are the critical link to fostering and expanding our vibrant, multicultural and diverse University community. As an Affirmative Action/Equal Employment Opportunity employer, UConn encourages applications from women, veterans, people with disabilities and members of traditionally underrepresented populations.

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