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A Multiple Input Multiple Output MIMO radar makes use of orthogonal transmit waveforms either in time, in frequency or in code, in order to exploit diversity gain (due to the larger number of degrees of freedom than their phase-array counterparts) and obtain more information from a radar scenario or target. Time Domain Multiplexing at transmit is an easy and cost-effective approach to achieve orthogonality but it implies increasing measurement time with the number of transmitter and a potential ambiguity for Doppler-shift estimation.

The range resolution of a radar system is directly propotional to its bandwidth. Applications demand more and more range resolution and thus higher high frequency bandwidths. Unfortunately, these bandwidths are limited because of several reasons like techical (hardware limitations), atmospherical windows and specific regulations. A promising approach to overcome these limitations is to use conventional small band radars with disjoint frequency bands and fuse the data using compressed sensing methods to gain a high overall bandwidth.

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Classification of SAR image data continues to be a big challenge. Major difficulties include the scarcity of available data, and the difficulty of semantically interpreting the SAR backscattered signal. There are no large-scale, SAR-derived image databases for Remote Sensing image analysis and knowledge discovery. Furthermore, while optical image classification has seen a breakthrough with the advent of Deep Learning methods that require Big Data, SAR-based systems have so far not experienced the same progress, likely because not enough data associated training labels is available.

Masters students, PhD students and Postdocs interested in the areas of signal processing, machine learning, medical imaging, communications and radar processing. Contact us.

The SAMPL Lab at the Weizmann Institute of Science offers a postdoctoral position within the project C'MON-QSENS! (Continuously Monitored Quantum Sensors: Smart Tools and Applications) funded by QuantERA EU program in Quantum Technologies. The appointment will be for a two years term, (possibly) renewable for a third year.

The SAMPL Lab at the Weizmann Institute of Science offers a postdoctoral position within the project C'MON-QSENS! (Continuously Monitored Quantum Sensors: Smart Tools and Applications) funded by QuantERA EU program in Quantum Technologies. The appointment will be for a two years term, (possibly) renewable for a third year.

PhD students and Postdocs in the areas of signal processing, machine learning, medical imaging, communications and radar processing: Host Professor: Yonina Eldar, department of mathematics and computer science, Weizmann Institute

The Speech Technology Group of Toshiba Europe LTD in Cambridge has opening for an ASR researcher. We are looking for candidates with background in signal processing, machine learning, acoustic modelling or expertise in building state-of-the-art systems for ASR.  The candidate should have a PhD in areas of speech technology related to automatic speech recognition, machine learning or a related field (Post-doctoral/industrial experience is beneficial). 

Signal Processing and Algorithm Engineer Are you a signal processing and algorithm engineer or data scientist with a broad skillset who loves to create, face difficult problems head on, and has a desire to always learn? Job Overview