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Field
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/ESA_selects_Harmony_as_tenth_Earth_Explorer_mission ) The candidate will develop and apply cutting-edge remote sensing or photogrammetry methods, in combination with data science approaches such as machine learning and data assimilation via
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hardware design using Verilog/SystemVerilog or equivalent HDLs. Sound knowledge of machine learning algorithms and their hardware implementation considerations. Demonstrated ability to conduct independent
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for a PhD Research Fellow position in fairness in artificial intelligence, available at the Department of Informatics, in the Scientific Computing and Machine Learning (SCML) research group. Starting date
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Vision Or Machine Learning. Strong publication record at the principal international computer vision and machine learning conferences. Sufficient theoretical and practical knowledge of methodologies
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, multimodal, and agentic AI, as well as foundation models, with a focus on geometric deep learning, large-scale knowledge graphs, and large language models. Fellows will also have the opportunity to apply
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chip packaging F5 Experience using data analysis or machine learning tools for electronics reliability or sustainability assessment F6 Experience with rapid prototyping technologies (3D printing, laser
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algorithms such as PINN, SKINN. Building agentic economic world models that are incorporated with theory and knowledge structures and connecting them with reinforcement learning and generative modelling
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/ESA_selects_Harmony_as_tenth_Earth_Explorer_mission ) The candidate will develop and apply cutting-edge remote sensing or photogrammetry methods, in combination with data science approaches such as machine learning and data assimilation via
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machines Machine Culture Ongoing work on social reinforcement learning and evolutionary optimization of social strategies Our aim is to advance the scientific knowledge of human-AI systems by understanding
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knowledge of machine learning models and Python tools for signal processing and machine learning. General knowledge of system architecture and APIs. Previous knowledge of physiological signal processing. 5