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<p class="MsoNormal">POST-DOCTORAL POSITIONS<o:p></o:p></p>
<p class="MsoNormal">University of Michigan<o:p></o:p></p>
<p class="MsoNormal">Human Neuromechanics Laboratory<o:p></o:p></p>
<p class="MsoNormal">http://www-personal.umich.edu/~ferrisdp/UMHNL.html<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">Two post-doctoral positions are available to work on studies examining the neural control and biomechanics of human locomotion. Both projects involve using high-density electroencephalography (EEG) to examine electrocortical dynamics during
walking and running. One position is available immediately (Project 1 below) and would require the post-doctoral researcher to be stationed in Ann Arbor, MI. Applicants do not have to be US citizens for this position. The second position (Project 2) is available
Nov. 1, 2011, and would require the post-doctoral researcher to be stationed in Aberdeen, MD, most of the time. The position would require travel to Ann Arbor, and applicants that are US citizens are greatly preferred.
<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">Applicants should possess a Ph.D. in Kinesiology, Engineering, Neuroscience, Physics, or related field. Must have strong technical skills and excellent MATLAB capabilities. Experience with human locomotion biomechanics, EEG, computational
neuroscience, and/or signal processing is highly desirable. Experience with EEGLAB, NFT, SIFT, and BCILAB is helpful.<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">Project 1: Electrical Neuroimaging of Brain Processes during Human Gait<o:p></o:p></p>
<p class="MsoNormal">There is an important clinical need to develop functional imaging techniques that can quantify brain processes during human locomotion and relate them to body dynamics. Mobile brain imaging could assist with the diagnosis and treatment
of patients with numerous movement disorders and neurological injuries. We propose that Independent Component Analysis of high-density electroencephalography (EEG) can quantify distinct brain processes involved in the control of human gait. Furthermore, we
contend that electrocortical brain processes identified using Independent Component Analysis of EEG correlate with whole body dynamics. We will study healthy young subjects performing various locomotor tasks while we record movement kinematics and 256-channel
EEG using active scalp electrodes. In Specific Aim 1, we will examine subjects walking at a range of speeds to determine if intra-stride patterns of activation and deactivation synchronized to the gait cycle are consistent across walking speeds. In Specific
Aim 2, we will examine subjects performing passive recumbent stepping and active recumbent stepping to determine the relative effects of sensory feedback vs. motor feed forward commands with sensory feedback on electrocortical brain processes. We hypothesize
that passive recumbent stepping will engage fewer electrocortical sources than active recumbent stepping. We will also compare active recumbent stepping with treadmill walking to determine the similarities between recumbent stepping and walking in activating
cortical brain processes. In Specific Aim 3, we will examine subjects walking on a split-belt treadmill to quantify sensorimotor hemispheric independence using coherence. In Specific Aim 4, we will study subjects walking on a narrow treadmill-mounted balance
beam to identify the electrocortical processes involved in maintaining and monitoring balance. The results from this study will advance our understanding of electrocortical dynamics related to the control of human walking, and will lead to new studies probing
mechanisms of neurological gait impairments. The findings could also facilitate new brain- machine interface technologies for controlling robotic orthoses or prostheses.
<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">Project 2: Ambulatory Neuroergonomics<o:p></o:p></p>
<p class="MsoNormal">High-density EEG and independent component analysis (ICA) can be used to study the cognitive processes that occur in the human brain during natural movements. We aim to demonstrate that electrocortical imaging is viable for humans walking
and running while they undergo complex locomotor tasks, including carrying loaded backpacks, traversing complex terrain, and attention-demanding scanning of the environment. Work will also include analysis of functional connectivity in electrocortical dynamics.<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">If interested in the positions, please send a letter of interest, CV, and names of three references to:<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">Dan Ferris<o:p></o:p></p>
<p class="MsoNormal">ferrisdp@umich.edu<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">The positions are open until filled. Review of applications will begin immediately.<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">University of Michigan is an equal opportunity employer.<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><span style="font-size:10.0pt">_______________________________<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:10.0pt">Dan Ferris, Ph.D.<br>
Human Neuromechanics Laboratory<br>
Department of Movement Science<br>
Department of Biomedical Engineering<br>
Department of Physical Medicine & Rehabilitation<br>
Neuroscience Graduate Program<br>
University of Michigan<br>
<br>
<a href="http://www-personal.umich.edu/~ferrisdp/"><span style="color:blue">http://www-personal.umich.edu/~ferrisdp/</span></a><br>
<br>
mailing address:<br>
Dan Ferris<br>
School of Kinesiology<br>
3158 Observatory Lodge<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:10.0pt">1402 Washington Heights<br>
Ann Arbor, MI 48109-2013<br>
<br>
e-mail: <a href="mailto:ferrisdp@umich.edu"><span style="color:blue">ferrisdp@umich.edu</span></a>
<br>
phone: (734) 647-2740<br>
fax: (734) 647-2808<br>
_______________________________<br>
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<p class="MsoNormal"><o:p> </o:p></p>
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