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Field
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models combined with the finite element method. Constitutive relations are required to describe material behavior. Advanced stainless steel typically possess complex microstructures across various length
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learning (ML) methods—including surrogate modelling, feature extraction, and inverse design algorithms Generate synthetic microstructures (based on the open-source OptiMic software) Perform descriptor
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, covering all cardiac conditions. This makes them unsuitable for identifying rare or complex cases, where annotations are scarce or unreliable. Recently developed unsupervised learning methods allow
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conditions at realistic, field-relevant scales. Developing a practical correction model to account for energy dissipation by flexible (vs. rigid) vegetation Original research on wave-induced forces and
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in their decisions and businesses in their strategies. Do you want to know more about LIST? Check our website: https://www.list.lu/ You will be hosted in the Process Modelling, Automation and
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-management and conservation practices": PhD student (f,m,div) in the Field of Geodata, Nitrogen and Soil Parameter Modelling Reference number: 18/2025/4 The salary will be based on qualification and research
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of waterlogged conditions, peatlands are projected to be particularly impacted by future climate change, through changes in both temperature and precipitation. Bioclimatic envelope models predict significant loss
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sources such as (i) atmospheric models, (ii) satellite remote sensing, (iii) land use information, and (iv) meteorological data. The aim of this PhD is to develop and implement models for integrating data
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a team of 25 colleagues dealing with CCUS, and industrial partners in Denmark as well as abroad. Your primary tasks will be to: Apply AI in context of capture solvent modelling Understand and analyse
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conditions. The specific aims are: To optimise large-scale production of a high-value carotenoid compound that is naturally released in nanoparticle form by a marine alga. Develop a mechanistic understanding