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- NTNU - Norwegian University of Science and Technology
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to accurate sample reconstructions using advanced signal processing and tomographic reconstruction algorithms. With the inclusion of noise the object estimation accuracy will be based on statistical concepts
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qualifications: Knowledge of polymer processing and statistical experimental design (DoE) Collaborative mindset and enthusiasm for working in interdisciplinary teams Strong organizational skills and a structured
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countries. The appointment is to be made in accordance with NTNUs guidelines for recruitment positions for general criteria for the position. Preferred selection criteria Experience with statistical analyses
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the year to assist scholarship administrators in monitoring available funding and fund utilization. Prepare scholarship-related reports, student data analyses, and statistical information as requested
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science. Electronic structure calculations (e.g. DFT or tight-binding methods), or thermodynamic modelling (e.g. statistical mechanics, MD or CALPHAD). Scientific data analysis. Interdisciplinary research
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at NTNU. We focus on long-term basic research and applied research at a high international level. Our aim is to meet the society’s needs for mathematical and statistical expertise in business and public
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; Proven competence on flow measurement techniques and PIV; Familiarity with optics, lasers, image processing and statistical data analysis Familiarity with flow modelling techniques (CFD) or machine
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. An example is the extension to turbulence statistics, rather than just mean velocity profiles. You will join the Process & Energy (P&E) department at TU Delft’s Mechanical Engineering faculty, working in a lab
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. We focus on long-term basic research and applied research at a high international level. Our aim is to meet the society’s needs for mathematical and statistical expertise in business and public
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-driven modeling or systems optimization. Experience 0–3 years of postdoctoral experience (or equivalent research experience) in computational, statistical, or data-driven modelling Proven experience in