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Shape the future of cancer research with AI-Driven 3D spheroid model simulations! Join us! We are seeking a motivated PhD candidate to join our interdisciplinary team bridging experimental in vitro work
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Integrated optics is currently experiencing unprecedented growth, driven largely by the rapid expansion of artificial intelligence (AI), cloud computing, and high-performance data processing
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Post-harvest pathology Biomarkers, volatiles, and sensors Cold chains and refrigeration technology Data analysis and modelling (R, Python, CFD) Besides that, you have demonstrable experience in project
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or neural networks) on CFD data to develop a fast, data-driven wind field predictor. You will combine this surrogate model with AeoLiS and evaluate the accuracy of the new model setup by applying it to
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to science, engineering and society. You will focus on optimization-based, data-driven and partially model-based control methods. You will have access to a strong research network and a broad range of
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models and monitoring data to assess its current structural state and predict its remaining lifetime. This will enable the condition of welded structures to be monitored throughout their service life
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capabilities interact with operational conditions, human intervention and the wider maritime and port logistics systems. The postdoctoral researcher will develop data-driven and model-based approaches to support
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software developers to integrate data‑driven models with mechanistic or physics‑based models and domain expertise; showing thought leadership on applying data & AI-solutions in the food & biobased domain
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Postdoc Position in AI Foundation Models for Crop Microbiomes Faculty: Faculty of Science Department: Department of Information and Computing Sciences Hours per week: 36 to 40 Application
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. The project will bridge wind farm aerodynamics, advanced control, system identification, filtering, and data-driven modelling, with a strong emphasis on combining physical knowledge with measurements rather