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flexibility. To fully unlock this potential, we need advanced tools that digitally replicate these networks and support optimized design and data-driven control strategies. As our PhD candidate, you will
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Organisation Job description We are seeking a candidate for a fully funded PhD position for the project DeCODA-LM – funded through the stimuleringsbeurs scheme of the Faculty of Arts. The project
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: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create
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: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create
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architectures, and on-device inference on edge-compute platforms. Demonstrated analytical problem-solving through experimental design, critical quantitative and qualitative data analysis, and validation
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testing, to achieve sub-second cycle times for robotic systems. 3. Demonstrated analytical problem-solving through experimental design, critical quantitative and qualitative data analysis, and validation
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Organisation Job description This fully funded PhD at the University of Groningen (NL) is an independent research project titled Where Rivers Speak and Landscapes Remember. The selected candidate
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We are looking for a talented and enthusiastic candidate for a fully funded 4-year PhD position. The PhD candidate for this project will be working at the RNA Structural Ensemble Dynamics group led
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Soils. • Knows, or is interested in, working with GIS/spatial data analysis, network analysis or modelling socio-economic structures. We offer an appointment in accordance with the Collective Labour
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. Proficiency in geospatial, 3D, and image-processing software for data collection and analysis. Experience working with GIS, QField, total stations, geophysical equipment, and drones. Experience in stratigraphic