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microstructural characterization, property testing, and failure analysis on the LPBF-processed functional materials A detailed investigation on the post-processing necessity and thermal treatment of the LPBF
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, complemented by quantitative LCA analysis. The outcome will be a decision support system (DSS) and methodology guidelines that support policy makers, industry, and vulnerable communities in making evidence‐based
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incorporated to ensure that the model outputs are applicable for an SMR-based nuclear power programme. Validation, sensitivity analysis and policy recommendations. To validate model results, benchmarks will be
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manufacturing, thermomechanical simulations, and process modeling (prior experi- ence in finite element analysis, computational thermodynamics, or residual stress modeling will be advantageous) Solid
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analysis by testing various in-situ applications such Energy Saving Devices. The collected data could be used to build a digital twin. The aim of this PhD project is to demonstrate clean maritime systems
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, or closely related topics. Interest in data analysis and computational modelling. Interest in software (cloud platforms/data visualization) and related applications to integrate real-world energy data. Very
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knowledge of data analysis and statistics. Data visualization and analysis in R The candidate should submit a research plan for the topic, including the overall research and data collection strategy
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., detailed research and time plan (laboratory work,data gathering, data analysis, interpretation of findings, writing up plan), and expected outcomes. The candidate can expand on the listed research questions
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data analysis Excellent written and spoken English communication skills The candidate MUST submit A cover letter expressing motivation to start the Ph.D. in this topic Curriculum Vitae, incl. details