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Field
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calculations, sample size determinations and statistical analysis plan. 3. Apply machine learning approaches to integrate diverse datasets collected from study participants to identify subtle differences
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Mobasher. It involves a diverse range of activities including: structural and geotechnical modeling, machine-learning model development, structural sensing and health monitoring, conducting physical
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conceptual DFT (linear response function, Fukui functions) or QTAIM theory (delocalization index), and their validation on a set of compounds known from the literature - interfacing a MLIP (Machine-Learned
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Science, Electrical/Computer Engineering, or a related field by the start date, with a strong publication record in computer vision, multimodal learning, or vision–language models. We require hands-on expertise with
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motivated post-doctoral associate with a strong background in control systems and machine learning to join the research team of Prof. M. Umar B. Niazi. The position focuses on the development of digital twins
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The Department of Electronic Systems at The Technical Faculty of IT and Design invites applications for a postdoc in the field of machine learning and decisions applied in cooling systems as per
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industrial conditions. Keywords: Artificial intelligence, autonomy, digital twin, edge computing, UAV systems. Objectives: Support the development of AI and machine learning algorithms for autonomous
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nuclear physics detectors. Experience analyzing data from high energy or nuclear physics experiments. Familiarity with Monte Carlo simulations. Familiarity with machine learning techniques. About the
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of physical systems AI-based condition monitoring Reinforcement learning Programming skills are required, with Python experience preferred. Theoretical understanding and hands-on experience with electric
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implement innovative architectures for real-time detection and control of laser processes. This interdisciplinary role combines artificial intelligence and machine learning with the physics of laser–matter