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aims to improve electrodialysis (ED) for REE separation by developing advanced membranes and integrating AI-driven optimization techniques. By combining materials innovation with machine learning
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mathematical modeling framework to find the optimal operation strategy for public transport services with autonomous vehicles Conduct computer programming to verify the efficiency of the designed solution
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such as miniaturization of NV sensors. Experience in systems engineering and process optimization is preferred. Key Responsibilities: Conduct research activities related to product design and engineering
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processes and develop innovative tools in cell biology. Key Responsibilities: Conduct experimental research using quantitative biochemistry, biophysics, and cell biology. Develop and optimize advanced
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conversion layers. The successful candidate will develop robust PQD/polymer composite films, optimize scalable film fabrication processes, and perform comprehensive optical and structural characterization. Key
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related processes for energy-efficient separations in areas such as energy, environment, and pharmaceuticals. This position offers the opportunity to contribute to high-impact projects and to work within a
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(specifically PCECs). Proven experience in developing and validating numerical models (e.g., using COMSOL). Hands-on experience with programming for numerical optimization, machine learning, and data processing
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research. Key Responsibilities: Develop and run a Cu–Cu hybrid bonding flow for fine-pitch 3D integration. Optimize process windows (pressure/temperature/anneal/surface activation) to minimize contact
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Conversion of Biomass” is looking for a Postdoctoral Researcher in Development of automated self-optimizing small-scale flow processes. The primary objectives are generation and optimization of automated flow
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interactions in vitro and in vivo. Here, the work will be devoted to the derivation, characterization and optimization of neural progenitor cells from human induced pluripotent stem cells for in vitro cell