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Autonomous on-board drone navigation (i.e., without human intervention) in inaccessible environments is a fundamental challenge. The goal in this project is to develop novel machine learning algorithms for autonomous drone navigation in outdoor environments including localization and synchronization for BVLOS (beyond visual line of sight) scenarios and/or GPS-denied environments, by utilizing RF signals from fixed ground stations and/or in collaboration with other drones.
Title: Sparse predictive models for the analysis and classification of pathological speech
Duration: from 01/11/2021 to 31/12/2022 (could be extended to an advanced position)
Digital Voice Systems, Inc. (DVSI) is seeking a qualified Speech Research & Development Engineer at our office in Westford, MA. This is a great opportunity to join our team of world class engineers in designing high quality voice compression technology that is implemented in hundreds of millions of telecommunication systems world-wide.
Lecture Date: May 25, 2021 -- Virtual Lecture
Chapter: Madras
Chapter Chair: S. Salivahanan
Topic: Making sense out of restless brain activity with computational neuroimaging
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Researchers in Speech, Text and Multimodal Machine Translation at DFKI Saarbrücken, Germany
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The MT group at ML at DFKI Saarbrücken is looking for
senior researchers/researchers/junior researchers
in speech, text and multimodal machine translation using deep learning.
June 4-5, 2021
Application submission deadline: May 10, 2021
Location: Virtual conference
Workshop Flyer
The Signal Processing (SP) research group at the Universität Hamburg in Germany is hiring a Postdoc (E13/E14) "Machine Learning for Speech and Audio Processing".
October 6-8, 2021
Location: Tampere, Finland
Wide-sense cyclostationary processes are an important class of non-stationary processes that have a periodic structure in their first- and second-order moments. This article extends the notion of cyclostationarity (in the wide sense) to processes where the mean and covariance functions might depart from strict periodicities and constant amplitudes.
In this paper, power allocation is examined for the coexistence of a radar and a communication system that employ multicarrier waveforms. We propose two designs for the considered spectrum sharing problem by maximizing the output signal-to-interference-plus-noise ratio (SINR) at the radar receiver while maintaining certain communication throughput and power constraints.