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The Department of Neuroscience at the Perelman School of Medicine, University of Pennsylvania, seeks an Assistant Professor in the non-tenure research track. Expertise includes high-density electrophysiology, optogenetics, and computational analysis of neural data with behavioral learning paradigms. Applicants must hold a Ph.D.
or equivalent. The successful candidate will develop an independent program focused on circuit-level sleep regulation in the mammalian brain and pursue extramural funding
Philadelphia, PA
Nov 05, 2027 at 11:59 PM Eastern Time
The Department of Neuroscience at the Perelman School of Medicine at the University of Pennsylvania seeks candidates for an Assistant Professor position in the non-tenure research track. Expertise is required in the specific area of state-of-the-art recording and manipulation techniques, including high-density electrophysiology, optogenetics, and computational analysis of neural data and proficiency with behavioral learning paradigms. Applicants must have a Ph.D. or equivalent degree.
Research or scholarship responsibilities may include the development of an independent research program focused on the circuit-level mechanisms underlying sleep regulation in the mammalian brain.
Candidates should have a distinguished record of scholarship, evidenced by publications on in vivo electrophysiology and on the neural control and function of sleep. The successful candidate will be expected to attract and maintain extramural funding. Teaching responsibilities may include training of graduate students and post-doctoral investigators.
This institution is using Interfolio's Faculty Search to conductthis search. Applicants to this position receive a free Dossieraccount and can send all application materials, includingconfidential letters of recommendation, free of charge.
The University of Pennsylvania is an equal opportunity employer. Candidates are considered for employment without regard to race, color, sex, sexual orientation, religion, creed, national origin (including shared ancestry or ethnic characteristics), citizenship status, age, disability, veteran status or any class protected under applicable federal, state, or local law.