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management (RDM) system. The goal is to create an overarching data space for the RTG that integrates various experimental techniques and simulation methods. This includes concepts for ensuring data quality
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future scenario simulation of VBD. Including machine learning, statistical, and process-based models. Present findings at scientific conferences and publish in peer-reviewed journals. Contribute
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Engineering, Information Systems, Mathematics, or a related field. Strong knowledge of software engineering (e.g., software architecture, development processes, quality assurance). Very good programming skills
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promising lean alloy system for additive manufacturing, as the mechanical properties can be tailored through phase composition, distribution and morphology by tuning process parameters. The work is carried
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Max Planck Institute for Demographic Research (MPIDR) | Rostock, Mecklenburg Vorpommern | Germany | about 14 hours ago
for the Studentship Programme, including: A copy of your Bachelor's academic transcript and certificate. A copy of your Master's academic transcript and certificate. If your Master's degree is pending, please provide
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focus on developing your PhD project In silico optimization of PBF-LB-manufactured Mg alloys. There is a plethora of studies on the processing, mechanical and corrosion properties of Mg-based alloys
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: Master’s degree in mechanical engineering, process engineering, chemical engineering, energy technology, or a related field Proven expertise in modeling and simulation; familiarity with CFD tools such as
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, process engineering, chemical engineering, energy technology, or a related field Proven expertise in modeling and simulation; familiarity with CFD tools such as COMSOL, Ansys Fluent, or OpenFOAM Excellent
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: we are conducting research on physical one-way functions, reproducible physical processes that generate measurable outputs from input parameters, but for which solving the inverse problem is difficult
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Particle Acceleration is looking for a PhD Student (f/m/d) Multimodal Reconstruction of Laser-Electron Accelerator Phase Space using Physics-Informed Deep Learning. Your tasks Understand the physical process