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Field
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theoretical foundation in one or more of the topics: Computational Mechanics, Finite Element Analysis (FEA), Numerical Optimization, or Materials Science. More specifically, we are looking for candidates with
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strong background in Mathematical Optimization and/or Numerical Analysis is desirable. Completed the previous degree with an excellent GPA (top 10% of class as a guideline) Proficiency in English to be
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. MINDnet aims at addressing the challenge through a holistic optimization - from individual computing devices to the overall architecture, including a focus on applications, and training methods - across
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Centre de Mise en Forme des Matériaux (CEMEF) | Sophia Antipolis, Provence Alpes Cote d Azur | France | 3 months ago
dozen passes are regularly made. One of the challenges of the project is to propose numerical approaches that enable these simulations to be carried out within a reasonable time frame, given the volumes
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-efficient, open-loop optimisation of fermentation control profiles, building on recent theoretical developments in optimal control theory, reinforcement learning and numerical methods as well as laboratory
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component, particularly magnetic components, Optimization and surrogate-modeling in Python, Integration of machine learning and numerical methods. We encourage applications from candidates with a strong
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Description The PhD researcher will work on the Inventory-Routing Problem with Pickups and Deliveries (IRP-PD) under demand and supply uncertainty. The IRP-PD requires the joint optimization of inventory and
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unique D-MIMO testbed at Lund University, extending existing and creating new deep learning-based models for anomaly detection, theoretical and numerical studies of detection quality, creating new
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existing and creating new deep learning-based models for anomaly detection, theoretical and numerical studies of detection quality, creating new distributed computational pipelines and optimizing
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interest in the topic, even if their background does not match every qualification listed above. Stipend 2: Data-driven modeling and optimization for efficient and secure-by-design Power Electronics (Aalborg