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theoretical understanding of statistical machine learning methods relevant to the project: Bayesian learning, machine learning, spiking neural networks. Experience of programming (e.g. with Python) and data
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: Statistical signal/image processing, deep learning, machine learning, neuromorphic computing Good communication skills and an appropriate publication record are essential. Solid knowledge of Python and C++ is
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researchers to find and follow their passion. We offer fantastic opportunities for learning, development and professional growth. This project will provide hands-on insight into, and potentially lead to, career
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. Proficient in Microsoft Office Software (Microsoft Word, Excel, PowerPoint), Scientific Data Analysis and Graphing Tools and other relevant computer-based tools used in a modern research environment
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grow? We encourage our researchers to find and follow their passion. We offer fantastic opportunities for learning, development and professional growth. This project will provide hands-on insight
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(https://cvn.centralesupelec.fr/ ), Prof. Pock from the Institute of Computer Graphics and Vision at Graz University of Technology (ICG ), Prof. Thiran from the EPFL Signal Processing Laboratories (LTS5