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Field
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to complex and overlapping pressures. Climate change, geopolitical tensions, energy risks, and shifting trade patterns make disruptions more frequent and difficult to manage. At the same time, companies must
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modelling and simulation of complex systems reinforcement learning or graph neural networks proficiency in Python and related computational toolchains a strong interest in interdisciplinary research bridging
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new machine learning methodologies that tackle unique computational problems in healthcare applications. We use large real-world complex datasets, including data extracted from electronic health records
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modelling, CFD mesh generation in complex 3D geometries. Proficient in handling large data sets and the ability to analysis and interpret results. Experience in commercial CFD package such as ANSYS package
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range of industries face the challenge of managing increasingly complex stochastic systems, where uncertainty is inherent and data is abundant. These systems arise in diverse domains—such as manufacturing
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part of the MARDATA doctoral network, the project “AI-derived thermodynamic parameters for aqueous modelling (AI-queous)” invites applications for a PhD position at the intersection of Computer Science
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data mining. The group provides a strong network to local AI expertise (e. g. Hessian.AI, TU Darmstadt), large scale compute infrastructure, as well as a broad international network (Stanford, UC San
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Location: Benguerir, UM6P Contract Type: Fixed-Term Contract (FTC) Duration: 2 years Start Date: As soon as possible Job Description: The specialist in urban energy networks is responsible
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Offer Description Project: EIC Pathfinder APACE nr 101161312 ‘Towards biomimetic sunlight pumped laser based on photosynthetic antenna complexes’ Description of tasks: synthesis of functional dyes
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. This position requires hands-on execution of complex experiments, meticulous sample processing, and contribution to data analysis and figure preparation. The scope of work will evolve with new projects and