[Comp-neuro] Postdoctoral Positions in Systems Neuroscience and Neuromorphic Engineering at Washington University in St. Louis

Barani Raman baraniwashu at gmail.com
Wed Nov 10 17:29:52 CET 2010


Dear Colleagues,



I would greatly appreciate your help in identifying interested candidates
for postdoctoral positions in Systems Neuroscience & Neuromorphic
Engineering in the Department of Biomedical Engineering at Washington
University in St. Louis.



Thank you,

Barani Raman







POSTDOCTORAL POSITION AVAILABLE IN SYSTEMS NEUROSCIENCE

-----------------------------------------------------------------------------------------------------



A postdoctoral position is available immediately in the Systems Neuroscience
and Neuromorphic Engineering Laboratory at Washington University in St.
Louis.



The main focus of research in my lab is to understand the design and
computing principles of biological sensory system using relatively simple
invertebrate models. To achieve this goal, we combine a variety of
electrophysiological recording techniques and computational modeling
approaches and study how the multi-dimensional and dynamic odor signals are
encoded as neural representations (odor coding) and processed by olfactory
circuits in the insect brain. In parallel, we apply these biological
principles to develop neuromorphic devices (‘electronic nose’) and
algorithms for solving parallel engineering problems.



More information can be found on the lab web site:

http://labs.seas.wustl.edu/bme/raman/



Successful candidate will have the opportunity to learn and combine
theoretical and experimental techniques to investigate fundamental
principles of neural computation. Qualified applicants are expected to hold
a doctoral degree in biomedical engineering, neuroscience, computer science
or in a related discipline. Applicants must have less than four years
postdoctoral research experience. Prior experience in single-unit/multi-unit
electrophysiology techniques is highly preferred. Proficiency in Matlab or
other programming languages is required. Highly competitive salary and
benefits are available and will commensurate with experience.



Washington University offers a highly collaborative, top-notch training and
research environment in computational and systems neuroscience. Wash U has a
very active and highly regarded neuroscience community, and there will be
ample opportunity for collaboration both within the department and with
faculty in the medical school.



Interested candidates should send their curriculum vitae, a letter of
interest outlining experience and research goals, and the names and contact
information of at least three references to:



Barani Raman

Assistant Professor

Department of Biomedical Engineering

2007 Brauer Hall

Washington University

One Brookings Drive

Campus Box 1097

St. Louis, MO 63130



Phone: 1-314-935-8538

Fax: 1-314-935-7448

Email: barani at seas.wustl.edu





*References:*



1. Temporally diverse firing patterns in olfactory receptor neurons underlie
spatio-temporal neural codes for odors

B. Raman, J. Joseph, J. Tang, and M. Stopfer

Journal of Neuroscience, Vol. 30, no. 6, pp. 1994-2006, February 2010



2. Frequency transitions in odor-evoked neural oscillations

I. Ito, M. Bazhenov, C. R. Ong, B. Raman, and M. Stopfer

Neuron, Vol. 64, pp. 692-706, December 2009



3. Sparse odor representation and olfactory learning

I. Ito, C. R. Ong, B. Raman, and M. Stopfer

Nature Neuroscience, Vol. 11, no.10, pp. 1177-1184, October 2008













POSTDOCTORAL POSITION AVAILABLE IN NEUROMORPHIC ENGINEERING

------------------------------------------------------------------------------------------------------------



A postdoctoral position is available immediately for a highly motivated
candidate in the Systems Neuroscience and Neuromorphic Engineering
Laboratory at Washington University in St. Louis.



The main focus of research in my lab is to understand the design and the
computing principles of biological sensory system and translate them to
neuromorphic devices and algorithms such as an ‘electronic nose’ for solving
parallel engineering problems.



More information can be found on the lab web site:

http://labs.seas.wustl.edu/bme/raman/



Successful candidate will have the opportunity to closely work with
neurophysiologists and develop non-invasive chemical sensing devices
(electronic nose) and bioinspired signal processing algorithms. Qualified
applicants are expected to hold a doctoral degree (Ph.D.) in math, physics,
computer science, engineering or in a related field, and have some
experience in one or more of the following areas: sensors, pattern
recognition, neural information processing, and intelligent systems.
Familiarity with chemical sensors is desirable but not required. Proficiency
in Matlab or other programming languages is required.



Washington University offers a highly collaborative, top-notch training and
research environment in biomedical engineering. Due to translational nature
of this work there will be ample opportunity for collaboration with the
faculty in the medical school.



Interested candidates should send their curriculum vitae, a letter of
interest outlining experience and research goals, and the names of at least
three references to:



Barani Raman

Assistant Professor

Department of Biomedical Engineering

2007 Brauer Hall

Washington University

One Brookings Drive

Campus Box 1097

St. Louis, MO 63130



Phone: 1-314-935-8538

Fax: 1-314-935-7448

Email: barani at seas.wustl.edu



*References:*



1. Designing and optimizing microsensor arrays for recognizing chemical
hazards in complex environments

B. Raman, D. C. Meier, J. K. Evju and S. Semancik

Sensors and Actuators B, Vol. 137, no.2, pp. 617-629, April 2009



2. A bio-inspired methodology for artificial olfaction

B. Raman, J. Hertz, K. Benkstein, and S. Semancik

Analytical chemistry, Vol. 80, no. 22, pp. 8364-8471, November 2008



3. Processing of chemical sensor array with a biologically-inspired model of
olfactory coding

B. Raman, P. Sun, A. Gutierrez-Galvez, and R. Gutierrez-Osuna

IEEE Transactions on Neural Networks, Vol. 17, no. 4, pp. 1015-1024, July
2006
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