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partner from data sciences provides data management and AI based Image analysis, an internal simulations group working on quantitative models to reproduce and predict experimental data, and an internal
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simulation scripts. TU Delft will support your research with access to the DelftBlue supercomputer for large-scale and intensive modelling. In the second phase, you will work / help our technicians
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developing custom Python-based simulation scripts. TU Delft will support your research with access to the DelftBlue supercomputer for large-scale and intensive modelling. In the second phase, you will work
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fiber orientation. Implement the developed models in commercial forming simulation software and validate their accuracy against forming experiments. We are looking for a colleague who is comfortable with
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passionate about sustainability, clean energy, and water treatment technologies?Are you skilled in machine learning, process modelling, or chemical engineering simulations?Are you excited by the idea
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-language models, or diffusion models to simulate and design complex urban traffic environments? Do you want to shape the next generation of data-driven mobility intelligence with your creative ideas and
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simulation : Aspen HYSYS/Plus. • Optimization skills: experience with GAMS or pyomo (or similar), including model formulation. • Life Cycle Assessment (LCA): experience with, e.g., Brightway2/SimaPro/Activity
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Your Job: You will work as a doctoral researcher within one of four interdisciplinary PhD projects in the Simulation and Data Lab Digital Bioeconomy. Each project combines natural sciences with
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 3 days ago
for osteosarcoma (OS) is hindered by limited knowledge of its biology and the lack of biologically relevant tools to test the efficacy of new approaches. This project aims to develop advanced 3D in vitro models and
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theoretical and practical limitations. Their results are often plagued by false positives (reporting problems that are not real) and false negatives (missing real issues). This PhD project aims to improve