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Field
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-driven modelling. Experience with numerical modelling, simulation, optimization, control, or engineering-data analysis. Good programming skills in Python, MATLAB/Simulink, or a comparable scientific
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are developing a suite of models to deliver a through-process microstructural and mechanical property prediction framework for steel. By integrating these models into a cohesive digital twin architecture, the work
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Max Planck Institute of Animal Behavior, Radolfzell / Constance | Radolfzell am Bodensee, Baden W rttemberg | Germany | about 1 hour ago
Great Apes” Our group We are seeking a curiosity-driven, collaborative PhD student to join the Minerva Fast Track Group “Culture and Social Behavior”, led by Dr. Zoë Goldsborough. The overall focus
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STLO) (https://eng-stlo.rennes.hub.inrae.fr/ ). This work is part of the “Predicting the browning of dairy powders by kinetic modeling of Maillard reaction and caramelization during drying and storage
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multidisciplinary environments Curiosity-driven and self-motivated working attitude Knowledge of biomechanical modeling, anatomy, vision-based motion capture, machine learning, control systems Keep in mind
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manufacturing approaches, investigating melt behaviour, densification, defect formation, and microstructure in materials. A distinctive element of the project is its data-driven approach. Together with colleagues
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physics-based and data-driven modeling and data-analysis skills (e.g. Python, MATLAB, or comparable tools) are an advantage High interest in interdisciplinary research Excellent communication skills and
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extra vacation days. Through the UU Terms of Employment Options Model, you can tailor your employment package to your needs. This way, we encourage you to grow in what you do, both in your work and your
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archaeologists to understand AI results – Generalization and transferability analyses, considering domain adaptation and transfer learning strategies to ensure model robustness across different geographic regions
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directions: Long-term Autonomy in Uncertain Environments a. Agentic Planning and Reasoning - Semantic Mission Planning with Foundation Models - Foundation models based task decomposition - Event-driven task re