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Field
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
Thermography. This raw dataset is needed to be processed and annotated to train supervised and unsupervised AI models. The research will aim to develop deep learning algorithms for damage classification
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Mathematics (Inverse Problems), Computer Science (Machine Learning, Computer Vision, Efficient Algorithms and High-Performance Computing), and Physics (Image Formation Modelling). Your project is part of
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Mathematics (Inverse Problems), Computer Science (Machine learning, Efficient Algorithms and High-Performance Computing), and Physics (Image Formation Modelling). Your project is part of the NXTGen High-tech
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algorithmic management in transforming organizational structures and labor relations The societal, political, and geopolitical implications of AI and related technologies The governance and regulation of AI
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correction and/or mitigation. Knowledge about networking protocols and distributed algorithms. Experience in programming, e.g., in C++, Python or Matlab. Experience with quantum simulators, such as NetSquid
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algorithms that align prefab factory production schedules with IWT capacity, terminals, and urban delivery windows. Model multi-level planning decisions, connecting early feasibility assessment and quotation
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planning, and explainable decision support. The PhD will operate across two worlds: The University of Twente — advancing scientific models, algorithms, and hybrid AI methodologies; Thales (the industrial
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 3 months ago
algorithms. We expect for the candidates to have a minimum of understanding in C/C++ and Python/Matlab. In addition, we are looking for candidates interested in application of numerics for physics and
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on stability. Testing the model in standard stirred tank apparatus Refining the model to allow predictability between different types of apparatus. Defining an algorithm for testing enzyme stability
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algorithmic solution development. The group focuses particularly on automated decision-making in autonomous cyber-physical systems, combining mathematical optimization, machine learning, and decision theory