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an excellent CV are strongly encouraged to contact the supervisor to discuss their opportunities. The ideal candidate has a Master degree in chemistry, physics, chemical engineering, or material science. Solid
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of material properties at the structural scale within the AMMETIS framework. Overall, this PhD project aims to contribute to the development of next-generation predictive tools capable of linking microstructure
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light at the quantum limit, and on the other hand to apply this knowledge in order to develop novel spectroscopic tools for medicine, biology and industrial material characterisation. The advertised PhD
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components for cochlear implants by applying your microengineering and material science skills? Here, we can offer you a unique opportunity to unfold your scientific creativity and inventiveness in a dynamic
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dissipation along the edges of the material. It is hoped that these sorts of materials will one day replace conventional silicon based electronics. This work is carried out within the Centre of Excellence
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activities in which you are welcome to participate. Website van de eenheid Project The acronym ODYSSEIA stands for: Organic Data Yields in Aegean Bronze Age material culture. Scientific, Sensory, Ethnographic
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are expected to have an excellent MSc degree in Chemical Engineering, Material Science, or Chemistry Experience and knowledge in material synthesis and/or (structural) material characterization are highly valued
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in AM enable the production of highly complex components, including multi-material parts, smart architectures, composites, and components with embedded electromechanical functionality. While
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developments in AM will reshape repair and remanufacturing practices within a circular economy. Recent advances in AM enable the production of highly complex components, including multi-material parts, smart
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data science and material design into a research approach of data-driven membrane discovery that includes material space construction and exploration, candidate selection and verification, providing data