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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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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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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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models. By utilizing biobanks of lung biopsies and established animal models, LifeLUNG will apply advanced machine learning and AI-driven deep sequencing to identify key immune factors and gene targets
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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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large research group which is well connected to the machine and transportation industry and I am eager to learn how academic research can be linked to industrial innovation roadmaps. - During my PhD I
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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
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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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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