Computational Imaging

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Assistant or untenured Associate Professor (Stanford University, Electrical Engineering)

The Department of Electrical Engineering at Stanford University (http://ee.stanford.edu/) invites applications for a tenure-track faculty appointment at the junior level (Assistant or untenured Associate Professor) in the broadly defined field of electrical and computer engineering. Priority will be given to the overall originality and promise of the candidate’s work over any specific area of specialization.

2 x Professor / Reader of Machine Learning and Artificial Intelligence

2 x Professor / Reader of Machine Learning and Artificial Intelligence

Department of Computer Science
University of Surrey
Guildford, UK

https://jobs.surrey.ac.uk/037121 

PhD Position in Computational Imaging

The Computational Imaging Lab in the Department of Computer Science at Portland State University is hiring a graduate student starting Winter/Spring 2022. This is a fully funded PhD student position and includes a monthly stipend and tuition waiver. The position will be for 1 year, initially, and will be renewed for up to a maximum of 5 years (subject to satisfactory progress and availability of funding).

Postdoctoral Position in Machine Learning-based Image Analysis (MGH and Harvard Medical School)

Closing date: open until the positions are filled.

The Gordon Center for Medical Imaging (GCMI) in the Department of Radiology at Massachusetts General Hospital (MGH) and Harvard Medical School (HMS) in Boston, MA has an immediate opening at the postdoctoral level to work on research projects related to PET and MR image analysis, image restoration and image reconstruction.

Signal Processing Engineer

Who we are looking for:
An experienced signal processing engineer who is creative, innovative, thrives on technical challenges, and is comfortable merging concepts from different technical disciplines.

Experience (required):
• 5 years of signal processing experience (analysis, modification, and synthesis)
• strong background emphasizing and detecting components in signals
• strong data analysis/data science abilities
• strong programming abilities

Sr Staff Signal Processing Engr / RF / Algorithms

JOB ID: 543945BRDate posted: Nov. 10, 2020City: OrlandoState: Florida

Description:Lockheed Martin is seeking a Signal/Image Processing Engineer for an exciting Orlando, FL position. The candidate will develop signal processing algorithms for complex RF sensors (passive and active sensors). Effort includes: Sensor algorithm design, integration, and test activities, coordinating sensor algorithm test activities with functional and Program Management. The candidate will also coordinate trade studies using an integrated flight simulation (IFS).

Postdoctoral Scholar

A postdoctoral scholar position with a focus on applications of machine learning in cardiac MRI. Details can be found at:

https://recruit.ap.uci.edu/JPF05862

Tomographic SAR Reconstruction (ESR8)

Applying tomographic SAR inversion using compressive sensing is well established in the SAR community. In contrast to state of the art approaches applied to satellite data novel CS reconstruction approaches combining sparsity with prior information will be researched and implemented. We intend to use high resolution airborne data sets from FHR and later, from our own sensor platform. The data is superior to satellite data concerning resolution und SNR. The main goal is the evaluation of the used CS methods for remote sensing 3-D imaging.

PhD Position in Efficient Very-Wide-Area ToF 3D Sensing by Means of Adaptive Compressive Sensing

A question that naturally arises in active sensing systems, such as ToF systems, is how much volume can be sensed with a given power budget, and how this can be extended by means of some more intricate sensing scheme. The main objective of this project is the development of a very-wide-area ToF 3D sensing system which has to be outstandingly efficient regarding the power consumption. To attain such an ambitious goal we propose bringing compressive sensing into the game and using recently proposed adaptive methods for constructing close-to-optimal binary sensing matrices.

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