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assets Practical experience in fuzzing or cybersecurity testing. Familiarity with machine learning concepts or AI platforms. Curiosity, creativity, and the drive to explore new research ideas. We offer
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that combines machine learning and knowledge-based inference. In real-world applications, it is often paramount to exploit expert knowledge for the task at hand. However, this poses significant challenges with
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engineering or mathematical engineering Good understanding of statistics and machine/deep learning algorithms Interest in Biomedical data science Excellent programming skills in Python Proficient English, both
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for the position are : Obtained a first class Master in a relevant field, e.g. computer science, biomedical engineering or mathematical engineering Good understanding of statistics and machine/deep learning
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resistance, via machine learning approaches. This doctoral project also foresees three secondments, each for the duration of three months, during which you will have the opportunity to visit partner
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power consumption trends or including the energy penalty of machine learning solutions themselves. And the energy efficiency at the transceiver hardware will be put in a broader perspective of
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representations in non-associative and associative learning and delineate the pathways and neuromodulatory systems underlying novelty-evoked exploratory behaviors. The research should integrate cutting-edge
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wireless communication, signal processing, digital, analog and mm-wave design, and machine learning. This is a unique opportunity to develop innovative, multi-disciplinary technology and shape future
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communications systems with experts in wireless communication, signal processing, digital, analog and mm-wave design, and machine learning. This is a unique opportunity to develop innovative, multi-disciplinary