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on the interplay between observations of natural phenomena, experimentation, and the modeling of the associated complex processes. ISTerre also conducts solid Earth observation missions, by hosting and
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). The project investigates how machine learning (ML) can be used to enhance the modelling of boundary layers in industrial CFD simulations, where complex geometries and computational constraints limit near-wall
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at elevated temperature, storing chemical energy while producing a concentrated CO₂ stream suitable for storage. Chemical looping oxygen carriers, such as Fe- or Cu-based materials, will be integrated with
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for fish, poultry, and pet food. Currently, the link between larval growth and future reproduction has not yet been established. This thesis, primarily experimental, will be based on a BSF mass rearing
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advanced data science methods, including statistical modeling and machine learning approaches Developing and applying novel causal inference methods, such as target trial emulation and causal AI frameworks
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., PsychoPy, E-Prime, Gorilla, Presentation). Hands-on experience in data visualization, data analysis, and programming in R and/or Python. Experience in, and aptitude for, complex statistical modelling (inc
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and Saeys teams. In this research project you will develop and apply algorithms to link clinical phenotypes of metastasis to molecular phenotypes in mouse models. It is known that metastases exhibit
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of objects, but current techniques are limited to small particles (micrometer to millimeter scale). In optics, the slowing down of light ("slow light") in structured media significantly amplifies radiation
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, FCVD creates a liquid-like layer that fills narrow trenches on substrates before solidifying into films. We will model this across multiple scales, from atoms to fluid flow, using quantum chemistry
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community stakeholders, are currently captured, stored and used. It will identify gaps, inconsistencies and missed opportunities for learning. Building on this analysis, the student will co-develop a