Post doctoral fellow or Research Associate
- Wayne State University School of Medicin
- Location: Detroit, MI
- Job Number: 7143231 (Ref #: req1031)
- Posting Date: May 2, 2023
- Salary / Pay Rate: postdoc: $50,000 or more
- Application Deadline: Open Until Filled
We seek to hire highly motivated scientists interested in neuroscience and vision research. Using the mouse retina as a model system, we examine retinal neural networks, synapses, and physiological outcomes. Mainly, we focus on (1) motion detection neural network and (2) ON and OFF neural signaling and light adaptation. The laboratory employs state-of-the-art techniques, including patch-clamp, Ca imaging with two-photon microscopy, multiple electrode arrays, immunohistochemistry, and AAV gene transfection.
The successful candidate should have a B.S., Ph.D., or equivalent in neuroscience, vision research, cell biology, or related fields. Expertise in patch-clamp is preferred but not required. Interested candidates should apply at https://waynetalent.csod.com/ux/ats/careersite/2/home/requisition/1031?c=waynetalent. Please select “Research Assistants/Associates” for position number req1031. Please attach a cover letter, curriculum vitae, and contact information for three references.
The Wayne State University School of Medicine’s Department of Ophthalmology, Visual and Anatomical Sciences ranks 11th in the nation in National Institutes of Health (NIH) research funding, including a National Eye Institute (NIH) P30 grant and a Research to Prevent Blindness grant. Our collaborative environment continuously supports motivated young scientists. Laboratory alumni have moved on their careers to become healthcare professionals, such as neuroscientists, medical doctors, pharmaceutical field, and computer professionals.
Our laboratory website: https://ichinose.med.wayne.edu/, Department: https://anatomy.med.wayne.edu/, and Twitter: https://twitter.com/WayneStateOVAS
Basic neuroscience research position. Using electrophysiology and Ca imaging with a two-photon microscope to examine retinal neural networks.