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Join TU Delft to uncover the biology of cellular robustness in an industrial yeast process and translate your discoveries into innovative genome engineering strategies. Job description You will join
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: Develop AI-assisted experimental workflows for oxide semiconductor deposition, aiming to accelerate process optimization and unravel new process–property relationships, and contributing to an EU Horizon
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nucleation pathways related to different emissions characteristics at the engine exhaust. The collected data would be helpful to validate the microphysics models for ice nucleation process, hence clarifying
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data would be helpful to validate the microphysics models for ice nucleation process, hence clarifying the different nucleation pathways for ice formation. You will collaborate with other researchers
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Are you interested in (re)entering biotech research? This position supports a non-linear career path with a focus on implementing process analytical technology into bioprocesses. Job description
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funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Leverage computer vision, smart
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Help accelerate the electrification of industry by combining molecular and process-scale simulations for high-temperature thermal energy storage. Job description Carbon-based chemicals are essential
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experimental PhDs and Canon Production Printing to enable data-driven ink optimization. Why Join? Work in the multidisciplinary Processing and Performance of Materials group Work at the forefront of sustainable
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: - A PhD degree in optimization or systems and control theory. - A strong mathematical background and an interest in conducting theoretical research. - A proven track record. - Excellent English
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the effects of optimized gene expression regulation on plant performance under optimal and field-like conditions at the Netherlands Plant Eco-phenotyping Centre. Your research aims to improve tomato Zn and Fe