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bipedal robot that will learn to walk on soft and natural ground, such as sand and gravel. The controller design will include knowledge of the type of ground the robot walks over, and how the substrate
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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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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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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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initiated research Advantages strengthening the candidate’s profile, but not explicitly required: Knowledge of machine learning and system optimisation; Python or MATLAB programming. Having published as (co
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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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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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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
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off-the-shelf sensors and the development of resilient algorithms that combine first-principles modeling with modern machine learning techniques. The goal is to push the boundaries of robust perception