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Field
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. You will perform microstructural characterization of dry coated electrodes using physical and machine learning based methods and the electrochemical assessment of the electrodes in battery cells. Your
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approaches (based on functional programming abstractions) to optimize the implementation of machine learning models and other digital signal processing algorithms on a specific FPGA architecture to fit within
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/Credentials/Licenses N/A Computer Skills MS Office and willingness to learn software used in the research lab Supervisory Responsibilities No Required operation of university owned vehicles No Does
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Engineering, Mathematics, Statistics, Computer Science or conjugate subject; strong record of publication in the relevant literature; good knowledge of machine learning algorithms and/or statistical methods
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cutting-edge big/deep data analysis methods, including machine learning and artificial intelligence. The ideal candidate will therefore have a strong background in data science and in the application and
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combines neuroscientific, musicological and psychological research in music perception, action, emotion and learning with the potential to test prominent theories of brain function and to influence the way
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and great opportunity of interdisciplinary training in machine learning and functional genomics. The project combines cutting-edge computational approaches, especially state-of-the-art machine learning
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-edge field of Human-Centered AI Technologies using advanced Generative AI and novel interaction technologies such as VR/AR and Eye Tracking. Potential Project Ideas are: 1. Multimodal Machine Learning
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, calibration, and the development of analysis tools and software. Our key focus areas are the physics of jets, top quarks, and EWSB, including the development of novel machine-learning methods for high-energy
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Agency (ARIA). The PROTECT project (Probabilistic Forecasting of Climate Tipping Points) brings together cutting-edge AI, statistical, and machine learning techniques with climate modelling, aiming