A postdoc in Compressive Sensing and an announcement for ICPRAM 2012 on High-Dimensional Inference from Limited Data: Sparsity, Parsimony, and Adaptivity

Amit Ashok sent me the following postdoc announcement:

Postdoctoral Position in Compressive Sensing at University of Arizona (College of Optical Sciences)=============================================================To apply go to: www.uacareertrack.com/applicants/Central?quickFind=202160  
The DARPA Knowledge Enhanced Compressive Measurement (KECoM) project has the primary goals of 

1. developing a mathematical framework for incorporating prior knowledge of tasks and observed signals into the design of compressive sensors, and 
2. applying this framework to relevant sensing modalities. 

Under the KECoM program, the UA is investigating information-theoretic techniques for sensor optimization under prior knowledge, as well as application to a compressive spread-spectrum receiver, a compressive radar transmitter/receiver, and a compressive spectral imager. 

An additional postdoctoral researcher position is available for the DARPA KECoM effort. Original postdoctoral appointment is for one year with possible renewal. Outstanding UA benefits include health, dental, vision, and life insurance; paid vacation, sick leave, and holidays; UA/ASU/NAU tuition reduction for the employee and qualified family members; access to UA recreation and cultural activities; and more!   

Duties and Responsibilities:

•  Provide advanced technical expertise in RF compressive receiver and compressive spectral imager design 
•  Provide technical expertise in manifold learning, Bayesian experiment design, and information-theoretic principles, such as rate-distortion theory, relating to estimation and  detection theory 
•  Periodic reporting and documentation as required by program timeline 
•  Occasional travel may be required  

Additional Minimum Qualifications     

•  Ph.D. in Electrical Engineering, Optical Sciences/Engineering, Mathematics, Applied Physics, OR related discipline 
•  Demonstrated experience in information theory, manifold learning, AND/OR statistical signal processing 
•  Demonstrated ability for independent research with associated publication record 
•  Demonstrated ability to work in a team environment 
•  Demonstrated ability to communicate effectively, both verbally and in writing  

                          Preferred Qualifications     

• Experience in compressive sensing and statistical inference 
• Experience in radar target recognition 
• Experience in numerical optimization techniques 
• Experience with one or more high-level programming languages (C, C++, etc.)

In a different direction, Rui Castro sent me the following:

Dear Igor,

I’m writing on behalf of myself and Jarvis Haupt from the University of Minnesota. We are organizing a special session on "High-Dimensional Inference from Limited Data: Sparsity, Parsimony, and Adaptivity" at the 2012 International Conference on Pattern Recognition Applications and Methods (ICPRAM). Our vision for this special session is to include contributions in a broad range of topics related to theory and methods for exploiting sparsity and other low-dimensional representations for high-dimensional inference tasks. The conference itself will be held February 6-8, 2012 in Vilamoura, Portugal. Additional information on the conference can be found at www.icpram.org, and further information on our (and other) special session(s) can be found at www.icpram.org/special_sessions.asp.

It would be great if you can announce this special session in your 'nuit-blanche' blog, as I believe there will be readers that might be interested in sending a contribution. Let me know if this is possible. I thank you in advance.

Best regards,

Rui Castro

It is possible.




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