CSJob: Signal processing summer internship Computational Sensing and Imaging Group, Rambus Labs, Sunnyvale, CA

You probably recall Patrick Gill from these entries:

• Calibrating and Enhancing the Planar Fourier Capture Array ?
• The In-Crowd Algorithm for Fast Basis Pursuit Denoising
• Calibration and Compressive Sensing Sensor Implementations

Well Patrick, is now at Rambus and he just sent me this awesome opportunity:

Hi Igor,

Thanks again for coordinating the Nuit Blanche blog, which continues to be a great way to keep up with the state of the art in compressive sensing. I have been continuing my research into tiny optical sensors at Rambus. We have had some big ideas recently, and we're looking for an algorithm and signal processing expert to spend a summer working with us. While the ad below targets Ph.D. students, we are also open to the possibility of an intern who already has their Ph.D. Compensation is very competitive; we would like to attract the best of the best. If you think Nuit Blanche readers might be interested, please feel free to post about this ad.

Best wishes,

Patrick R. Gill

Thanks Patrick , here is the announcement

Signal processing summer internship

Computational Sensing and Imaging Group

Rambus Labs

Sunnyvale, CA

The Computational Sensing and Imaging Group within Rambus Labs continues to develop new classes of optical sensors.  We are seeking a highly qualified signal processing engineer to assist an active research team in the invention and implementation of numerically-efficient algorithms for image processing, computer vision and optical sensing based on the measurements these devices make.  This summer internship position affords the opportunity of patenting as well as publishing new mathematics and algorithms related to our research.

Candidates should have the following qualifications:

• BS or MS degree in mathematics, electrical engineering, physics, computer science or a closely-related discipline and current enrollment in a relevant graduate program or substantial, relevant, outstanding work experience
• Facility implementing numerically-efficient solutions to inverse problems in MATLAB, C or C++, including multicore and networked environments
• Innovation in numerically-efficient methods of implementing sparse priors for image reconstruction would be an asset
• Experience in generalized convolution and deconvolution with spatially-varying kernels desirable
• Strong knowledge of algorithms in computer vision, image processing and pattern recognition
• Strong verbal and mathematical communication skills
• Experience with cluster computing and GPGPU programming
• Legal permission to work in the USA

Rambus Inc., is located in Silicon Valley/Bay Area, near cultural centers such as San Jose and San Francisco, academic centers such as Stanford University and U. C. Berkeley, and many spectacular natural destinations such as Yosemite National Park, Lake Tahoe, Big Sur, Marin Headlands, Sonoma Valley, Napa Valley, ….

To apply:  Go to this link.

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