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data (e.g. instrumental, laboratory, environmental, numerical and categorical data, text, geospatial data or time series); c) Experience in Python programming and in data analysis and machine learning
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pumping technologies for future electrified energy systems. We are currently recruiting a PhD candidate at DTU for a project on the multi-physics modelling of bearingless pumps. A parallel PhD position is
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systems are generally ill-conditioned. The project sits at the intersection of classical numerical analysis, scientific machine learning and computational chemistry. Based on regularization techniques and
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future of Austria’s most attractive campus university? We currently have a job opening for a: PhD student for numerical modelling of mass transfer in fluidised beds (must hold a Diploma/Master's degree
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analysis (FEA) and numerical modelling, preferably using Abaqus. Good programming skills, preferably in Python. Ability to work effectively both independently and as part of a multidisciplinary research team
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metabolomics gained during their PhD, covering the entire analytical workflow, from sample preparation to data analysis. A good understanding of plant metabolism is also desirable. Skills ➢ Qualifications
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companies. The research will integrate techniques of numerical analysis and structure-preserving algorithms to generative modeling in AI. It will build upon the work done at IMF and SINTEF in this field. We
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project. Computational mechanics PhD projects PhD 1: Rolling contact fatigue in green bearing steels – numerical microstructural modelling [SKF; Ron Peerlings] PhD 2: Predictive analysis of edge crack
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experience with Linux is therefore also required • Candidates with a completed PhD degree before the interview date will also be considered • Documented research experience on numerical modelling
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inverse problems, as well as the development of numerical methods that can eventually be applied to large-scale wave-imaging problems. The PhD project will have a strong mathematical component. You will