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-physics systems, particularly thermal-mechanical analysis in metal additive manufacturing. Familiarity with finite element/finite volume methods, high-performance computing, and simulation data processing
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functions associated with the failure mechanisms using high-fidelity Finite Element Analysis. Perform sensitivity and uncertainty analysis to uncover the most significant variables in the derived limit states
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exhibiting magnetovolume coupling and/or negative thermal expansion; thermal, magnetic, morphological, and structural characterization; magnetic and structural analysis; preliminary experience with finite
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codes, finite element or finite different methods, peridynamics, phase field models, multi-objective optimisation methods, CAD. Demonstrated ability to adapt to fast-changing project direction and learn
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Health Monitoring (SHM) and Weigh-In-Motion (WIM) systems integrated with advanced probabilistic methods, machine learning and Artificial Intelligence (AI) approaches, and 2) advanced Finite Element (FE
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methodology for steel fibre reinforced concrete structures assisted by nonlinear finite element analysis and artificial intelligence tools”, project number 16782, code operation COMPETE2030-FEDER-00796500
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suitable for a PhD education. You must meet the requirements for admission to the faculty's Doctoral Programme Excellent oral and written presentation skills in English Solid knowledge in finite element
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methodology for steel fibre reinforced concrete structures assisted by nonlinear finite element analysis and artificial intelligence tools”, project number 16782, operation code COMPETE2030-FEDER-00796500
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to efficiently create new, sustainable and recycling-adapted structural metals. Alloys with a reduced number of elements, so-called lean alloys, and material systems with a high tolerance to impurities from
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: Master's degree in Mechanical Engineering, Ocean Engineering, Materials Engineering, Naval Engineering, or related fields, with a solid background in structural dynamics, finite element analysis, and