A postdoctoral/research associate position in computational neuroscience is available immediately in the NIH funded project focusing on multiscale computational modeling of interactions between respiratory central pattern generator and sympathetic nervous system as it relates to neurogenic hypertension. This collaborative project is performed by the groups of Yaroslav Molkov (Dept. of Mathematical Science, Indiana University – Purdue University, Indianapolis, IN, USA), Ana Abdala (University of Bristol, UK) and Daniel Zoccal (Sao Paulo State University, Brazil). Excessive sympathetic activity plays a crucial role in the development and maintenance of hypertension. Such autonomic dysfunction is observed in hypertensive patients with obstructive sleep apnea (OSA). Chronic exposure to intermittent hypoxia (CIH) that occurs in OSA is the main factor leading to sympathetic overactivity and hypertension. A CIH-driven increase in sympathetic output is largely dependent on the emergence of active expiratory pattern. The respiratory central pattern generator (rCPG) is composed of two interacting oscillators. The first occupies Bötzinger/pre-Bötzinger complexes and generates self-sustained respiratory rhythm controlling the diaphragm to provide inspiration. The second oscillator, the parafacial respiratory group (pFRG), resides in the retrotrapezoid nucleus (RTN). The RTN/pFRG oscillations emerge in hypoxic and hypercapnic conditions, and drive motor output to abdominal muscles for active (forced) expiration. Interactions of these respiratory circuits with the sympathetic neurons of the rostral and caudal ventrolateral medulla evoke respiratory-related oscillations in sympathetic efferent drive. Exposure to CIH leads to alterations in excitability of RTN/pFRG neuronal population and/or modifications in synaptic connections between respiratory oscillators and sympathetic neurons which ultimately results in the elevated baseline sympathetic activity and arterial pressure. This interdisciplinary project aims to reveal the mechanisms that couple breathing and control of blood pressure in the brain in health and disease, and for the first time translate them into a realistic computational model. Such a model will have the unprecedented potential for generating effective non-pharmacological means of controlling blood pressure and breathing via implantable biofeedback devices (e.g. vagus nerve stimulation) and non-invasive devices for guided control of autonomic function (e.g. device-guided paced respiration). Furthermore, it will provide a robust scientific substrate for evaluating the usefulness and safety of alternative medicine interventions, such as controlled breathing practices, for lowering blood pressure and improving heart rate variability. Applicants must have a PhD degree in Neuroscience, Applied Mathematics, Physics, or a related discipline and have excellent programming skills (C++, Matlab, UNIX). Previous experience in computational neuronal modeling is a plus. Interested candidates are encouraged to contact Dr. Molkov ( ymolkov@iupui.edu) by email. To apply, please send an email along with (1) curriculum vitae; (2) a cover letter describing previous research experience and interests; (3) the names and contact information of three references. Application processing will begin immediately and the search will remain open until the position is filled. Best Regards, Yaroslav Molkov, Ph.D. Assistant Professor Indiana University - Purdue University Indianapolis Department of Mathematical Sciences 402 N. Blackford St, LD 270, Indianapolis, IN 46202 Office: LD 224U Phone: (317) 274-6934 Fax: (317) 274-3460 Email: ymolkov@iupui.edu