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Field
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-of-the-art statistical approaches. Actively communicate results to the developers of predictive models within ReDiLEEP. Disseminate your research through publications in leading international journals and
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, and control (such as CNNs, RNNs/LSTMs, autoencoders, physics-informed neural networks, anomaly/outlier detection, uncertainty quantification, model predictive control). Documented knowledge and
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the SYCL programming model Personal characteristics To complete a doctoral degree (PhD), it is important that you are able to: Work independently Work in a structured way, set goals and make plans to achieve
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, France to complete the project. Objectives The objective of this PhD project is to develop advanced numerical modelling tools to support the digital twins of refractory materials, with the aim
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greenhouses than constructing detailed CFD models for each location. Key expected innovations in this project are expected to include a hybrid data-driven and model-based predictive control approach that uses
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when using closed, proprietary models, where model weights, training data, and internal representations are inaccessible. The PhD project will therefore investigate how trustworthy agentic AI systems can
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-pulse laser micromachining facilities to develop crack-free laser texturing strategies for ceramic materials. Establish predictive models linking laser processing conditions to feature geometry and crack
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Stage Researcher (R1) Positions PhD Positions Application Deadline 21 Sep 2026 - 23:59 (Europe/Oslo) Country Norway Type of Contract Temporary Job Status Full-time Is the job funded through the EU
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the position We are seeking a highly motivated PhD candidate to investigate cascading cyber effects, cyber resilience, and advanced cyber range modelling. The research combines simulation, software
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4th October 2026 Languages English English English The Department of Information Security and Communication Technology has a vacancy for PhD Candidate in Modelling and Executing Cascading Effects