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Field
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energy piles have been extensively studied, using field tests, physical modelling, and numerical modelling, the behaviour of energy piles under complex thermomechanical loading (e.g. vertical-horizontal
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transition. See: https://www.tudelft.nl/en/2026/tbm/tpm-researchers-receive-nwo-kic-consumer-behaviour-for-a-circular-system-transition-grant . The project includes 2 PhD positions, 2 Postdoc positions, and
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(materials, scenarios) - Translation of local knowledge into simulation rules - Facilitation or co-facilitation of model testing sessions - Collection of feedback for prototype iterations. Analysis and
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headquarters in Trondheim. At NTNU, 9,000 employees and 43,000 students work to create knowledge for a better world. You will find more information about working at NTNU and the application process here
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research aims to uncover causal human brain circuits underlying emotion and cognition and advance mechanistically informed precision neuromodulation for brain disorders. Our framework integrates brain
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 3 months ago
additional days per year, including your birthday Minimum Requirements: PhD in Engineering Experience in Machine Learning, Deep Learning, reduced-order modeling, or physics-informed models Knowledge
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. The PhD student is expected to develop and apply methods for causal inference will be part of the SMARTbiomed Pioneer centre https://SMARTbiomed.dk/about-SMARTbiomed. Project Description The PhD project
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modelling. References/further reading Wang, X. Q. et al. Spatial predictors of immunotherapy response in triple-negative breast cancer. Nature 621, 868-876 (2023). Danenberg, E. et al. Breast tumor
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characterization of materials’ magnetic, electronic and structural properties. Experience in spectroscopy and microscopy is valuable Knowledge in programming (Python) and 3D modelling will be valuable Availability
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performance simulation, lifecycle assessment, or climate resilience. Knowledge of uncertainty quantification and risk modelling is desirable. You have experience with programming and data analysis (e.g., Python