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Field
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. Until now, specific EN fingerprints of localized corrosion are determined manually. This is a tedious procedure that requires considerable expert knowledge. Artificial intelligence or machine learning (AI
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Universidade Lusófona´s Research Center for Digital Human-Environment Interaction Lab | Portugal | about 1 month ago
Python Machine Learning Libraries (PyTorch, Keras, etc.); statistical and machine Learning expertise and supervised and unsupervised methodologies; Valuable Bonus Skills include: experience with Unity3D
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Are you highly motivated to do PhD research in mathematical machine learning, with special emphasis on mathematical foundations for explainable AI? If yes, the Korteweg-de Vries Institute
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mathematical control theory, and a keen interest in machine learning to apply for the PhD position within the Dynamics and Control section at the Department of Mechanical Engineering, Eindhoven University
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computational neuroscience, connectomics and/or Machine Learning is appreciated. Our goal perform connectome analysis on neuroimaging data\integrate connectome findings across multiple speices work on developing
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of embedded machine learning, neuromorphic hardware and deep learning accelerators. Want to get more information? Click here. What you will do Responsible for RTL design (VHDL, Verilog) of digital blocks and
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candidate will play a key role in designing and implementing innovative solutions at the intersection of sensor data collection, machine learning, and real-time decision-making. Specifically, the candidate
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to support coordinated decision-making for sustainable strategies in the port call? As a PhD student at TU Delft, you will leverage AI (i.e. optimization and machine learning techniques) to prepare ports
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. optimization and machine learning techniques) to prepare ports, terminals, shipping companies, and other port actors for this important challenge. Your research will be part of the PortCall.Zero project - a five
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with e-CALLISTO instruments or Software-Defined Radios (SDRs). · Familiarity with machine learning for astrophysical data analysis. · Knowledge of solar radio data pipelines and event classification