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be involved in the three-year project “High Dimensional Hierarchical Optimization methods for Machine Learning and Stochastic Optimal Control”. Background or expertise in one or more of the following
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, processing optimization, and experimental troubleshooting Materials characterization using techniques such as GIWAXS, Raman, FTIR, UV-vis, and electrical transport measurements Understanding structure-property
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Thin-film fabrication, processing optimization, and experimental troubleshooting Materials characterization using techniques such as GIWAXS, Raman, FTIR, UV-vis, and electrical transport measurements
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-transport-layer engineering, dark-current suppression, metasurface integration, optical-field manipulation, and low-noise detector characterization. The successful candidate will translate optimized CQD
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optical, electronic, and photodetector properties. Responsibilities Synthesize III–V CQDs using air-free colloidal methods. Design and optimize precursor chemistry for InAs-, InSb-, Ag₂Te-, and PbSe/PbS
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to extrusion and compounding Develop insights into interfacial stability, flow instabilities, and morphology control in multiphase and multilayer systems. Support and optimize advanced polymer processing
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, the generated data can be used to optimize mineral extraction processes from existing mines within a geometallurgical framework. The position will mostly focus on the development of measurement protocols and data
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, Sputtering or MOCVD systems for microelectronics and emerging sensor technologies. Key Responsibilities: Develop and optimize wafer-scale 2D materials, including TMDCs, MXenes, and MOFs, for microelectronics