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PhD position, Next generation Neural NetworksPosted by: University of Antwerp
Posted date: 2019-Apr-17
imec is the world-leading research and innovation hub in nanoelectronics and digital technologies. The combination of our widely acclaimed leadership in microchip technology and profound software and ICT expertise is what makes us unique. By leveraging our world-class infrastructure and local and global ecosystem of partners across a multitude of industries, we create groundbreaking innovation in application domains such as healthcare, smart cities and mobility, logistics and manufacturing, and energy.
University of Antwerp – imec IDLab Research group
The IDLab research group of imec and the University of Antwerp performs fundamental and applied research on internet technologies and data science. The overall IDLab research areas are machine learning and data mining; semantic intelligence; distributed intelligence for IoT; cloud and big data infrastructures; multimedia coding and delivery; wireless and fixed networking; electromagnetics, RF and high-speed circuits and systems. Within Antwerp, IDLab specifically focuses on wireless networking and distributed intelligence. IDLab has a unique research infrastructure used in numerous national and international collaborations.
IDLab collaborates with many universities and research centres worldwide and jointly develops advanced technologies with industry (R&D centers from international companies, Flanders’ top innovating large companies and SME’s, as well as numerous ambitious startups).
For further development of the IDLab machine learning research cluster, we are looking for a PhD researcher in the domain of next generation neural networks.
The research project
State-of-the-art artificial neural networks have achieved remarkable successes in terms of accuracy in a variety of AI-related tasks. Part of this success is due to the availability of huge amounts of (labeled) data and ample computing power for off-line training. However, in many real-life applications there is a need to be able to train or online adapt these networks with only limited amount of labeled data, and robust networks that can be executed on small and low power devices.
In this research project, you will investigate new brain-inspired ideas that go beyond the current 2ndgeneration networks (e.g. spiking neurons, temporal coding, learning with hyper-vectors, …) with the aim of designing solutions with high accuracy, but that can also learn new concepts from only a limited number of examples, are robust to noise, and allow for low power implementations.
For more information, please contact Hanne.Evertsuantwerpen.be