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Reality, and mobile computing in general. Job description Literature review of machine learning techniques on signal and time series analysis (specifically IMU, EMG, PPG, microphone, gaze), including
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from the raw data provided by the multimodal sensors. Literature review of machine learning techniques on signal and time series analysis (specifically EMG), including Multivariate Time Series Analysis
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computer science and applied mathematics to develop state-of-the art generative machine learning models to design improved catalysts for these reactions. Your profile We are looking for a committed and motivated
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requirements for the data analysis and visualization of the results based on literature and clinicians’ input. Set up study protocol for a combined rTMS and NIRI stroke rehabilitation approach. Select, implement
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recorded by various instruments, including distributed acoustic sensing, acoustic emission sensors, and geophones. With these efforts, the PhD candidate will improve the current state-of-the-art of real-time
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and professional skills. Your profile Educational Background: Applicants must possess a Master of Science (MSc), Master of Arts (MA), or Master of Philosophy (MPhil) degree in business administration
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(at the time of the magma ocean) to the present day. We are using state-of-the-art numerical simulations to reproduce as realistic a picture as possible of the processes at work and the climate of the planets
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product development that are not yet state of the art. The project of the PhD position is embedded in a close collaboration with Swiss industry partners. Job description The position offers the possibility
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to decipher the function of the Type III secretion system 1, enterocyte manipulation by the translocated effector proteins and the host’s innate immune defence. Selected literature: Fattinger, S.A., Böck, D
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international city with broad access to outdoor activities, arts and culture, and other European cities, as well as a rich and excellent scientific community. In this context, we offer: Interdisciplinary research