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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
produced by PBF-LB. After identification of the most relevant parameters adopting a design of experiments strategy, a probabilistic (e.g. Gaussian Process Regression) model to describe the relationship
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» Materials engineering Engineering » Simulation engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Belgium Application Deadline 31 Oct 2025 - 02:30 (Europe/Brussels
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tools for static and dynamic analysis are powerful for detecting vulnerabilities, they suffer from both theoretical and practical limitations. Their results are often plagued by false positives (reporting
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dynamics to neuroaesthetics Modelling Oscillations in Human Immune & Neuroimmune Cells Multi-level modelling of neuromodulation and lesioning Multimodal Machine Learning for Psychological Profiling
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machinery. These tasks include the verification of backlash detection and monitoring strategies formulated from the integration of multibody models and sensor data, as well as their subsequent development
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machinery. These tasks include the verification of backlash detection and monitoring strategies formulated from the integration of multibody models and sensor data, as well as their subsequent development
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sciences, economics and regulation. Job description The project of the PhD student based at CWI in Amsterdam will focus on techno-economic models (and in particular multi-agent modeling) of energy exchange
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geometry and integrity. Objective 2: Develop and implement simulation models in ANSYS Fluent to investigate the two-phase printing and droplet freezing processes, providing insights into the coupled effects
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computational fluid dynamics and numerical modelling will be used to simulate performance under varying runoff scenarios, pollution loads and climate conditions. By developing advanced road gully designs with
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versus unmodified trees. Laboratory simulations and growth experiments will explore mistletoe’s physiological responses to climate stress. Training The project provides an exceptional interdisciplinary