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Field
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computing needs, and enabling rapid responses to potential issues in remote locations. The aim is to develop robust and scalable software solutions suitable for practical industrial deployment on a large
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Generate synthetic microstructures (based on the open-source OptiMic software) Perform descriptor extraction and micromechanical simulations (MCRpy, DAMASK) Vary the material processing parameters, which
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new nationwide AI system can be predicted using generated data sets of different sizes and measuring the environmental impact. This impact can be measured and calculated by our Software Energy Lab
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process. Together, these innovations aim to make column generation more practical for solving real-world, large-scale optimization problems. These innovations will be tested within a structured software
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proof-of-concept software tools Machine learning is a plus Strong analytical and programming skills are required (Python, Matlab, and C/C++). Prior proven experience in data-driven innovation projects is
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Engineering, or related fields. Solid background in structural dynamics, wind engineering, and finite element modelling. Experience in programming (MATLAB/Python) and/or structural analysis software (e.g
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/or interest in programming languages (e.g. MATLAB, Python, R) and software platforms such as Autodesk, ALLPLAN, ANSYS, REVIT, Tekla, Rhino, Grasshopper, etc. Basic knowledge in the areas of signal
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engineering and wave-wind theories is advantageous Experience in coding (e.g., Python) and in the use of Structural Analysis Software (e.g., OpenSees, Abaqus) is highly desirable Ability to work independently
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(applied mathematics, software engineering, and medicine), it is expected to refine the scope and goals of the project with the selected applicant, depending on technical skills and personal interests
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modelling software. Practical experience in advanced manufacturing techniques for novel materials. Opportunities to present research at international conferences and build a professional network across