Job Information
University of Connecticut (UConn) Postdoctoral Research Associate in Storrs, Connecticut
JOB SUMMARY
The laboratory of Dr. Scott Rich in the Department of Physiology and Neurobiology at the University of Connecticut, Storrs is seeking a Postdoctoral Research Associate to explore the role of heterogeneity in maintaining physiologically relevant neuronal microcircuit activity. This research will take place in a “dry,” computational lab, utilizing techniques ranging from the creation of biophysically detailed models of individual neurons to the simulation and study of neuronal microcircuits. While a primary focus of the lab is the study of heterogeneity’s influence on oscillatory dynamics in the cortex, the postdoc’s research program could conceivably shift its focus to other brain regions and/or network dynamics of interest.
Given the uniquely interdisciplinary and collaborative nature of computational neuroscience research, viable candidates may hold their Ph.D. in fields including, but not limited to, Mathematics, Biomedical Engineering, Neuroscience, Biology, and Physiology. Regardless of the field of their Ph.D., candidates whose doctoral training fell under the broad banner of “computational neuroscience” are encouraged to apply, especially those with training or interest in the study of spiking neuronal microcircuits.
The University of Connecticut is rated first among public universities in New England and in the top 20 nationwide, is located in northeastern Connecticut with easy access to Boston and New York City. The University’s Department of Physiology and Neurobiology is a vibrant, collaborative environment that will provide exposure to a vast array of neuroscientific topics, including opportunities to directly collaborate with experimentalists. The web page of the Department of Physiology and Neurobiology, including information on Dr. Rich’s lab and research interests, can be found at www.pnb.uconn.edu.
DUTIES AND RESPONSIBILITIES
Design and execute computational experiments:
Design model neurons, with an appropriate balance of computational tractability and biophysical detail, incorporating experimentally characterized neuronal heterogeneities.
Create model neuronal microcircuits including synaptic and input heterogeneities.
Execute simulations in a computationally efficient manner.
Data analysis:
Apply appropriate measures to quantify dynamics of in silico simulations, and design new measures when necessary.
Present these data and measures in a visually appealing and accessible fashion in lab meetings, conferences, and publications.
Mentor graduate and undergraduate students:
Serve as a mentor and role model for junior lab members, including providing constructive feedback and being accessible for impromptu questions.
If the candidate aims to pursue a career in academia, more directly supervise students, including designing feasible research programs.
Uphold the code of conduct as described in the Rich Lab’s “mentor-mentee contract.”
MINIMUM QUALIFICATIONS
A Ph.D. in any of the interdisciplinary fields associated with computational neuroscience; more importantly, the content of their doctoral thesis must include both a significant computational and neuroscientific component.
Interest in understanding the effects of heterogeneity on the dynamics of neuronal microcircuits.
Mathematical training past the level of introductory differential equations.
Excellent coding skills.
Strong scientific communication skills, particularly the ability to “liaise” across scientific disciplines including neuroscience, mathematics, engineering, and computer science.
Self-motivated and the ability to work independently.
PREFERRED QUALIFICATIONS
Mathematical training up to and beyond the study of dynamical systems and numerical analysis.
Expertise coding in Python and MATLAB, including the maintenance of code repositories.
A strong background in the foundations of neuroscience, including exposure to both in silico and in vitro experimental techniques.
Experience creating and studying in silico neuronal microcircuits.
APPOINTMENT TERMS
This is a full-time, 12-month position with the potential for annual renewal based on performance and funding.
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 https://hr.uconn.edu/jobs, Staff Positions, Search #498073 to upload a resume, cover letter, and contact information for three (3) professional references. Review of applications will begin on January 15, 2024, and continue on a rolling basis until the position is filled.
All employees are subject to adherence to the State Code of Ethics which may be found at http://www.ct.gov/ethics/site/default.asp.
All members of the University of Connecticut are expected to exhibit appreciation of, and contribute to, an inclusive, respectful, and diverse environment for the University community.
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, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
The University of Connecticut is an AA/EEO Employer.
