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to optimize performances. The postdoc will carry out structural and morphological characterizations (X-ray diffraction, TOF-SIMS, AFM, and microscopy) of the selected superconducting materials. In the second
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research in radiochemical separations and advanced aqueous recycling of used nuclear fuel (UNF). The successful candidate will contribute to the development and optimization of advanced aqueous recycling
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candidate will contribute to cutting-edge research in optimal control theory, differential game theory, mean-field game theory, and mean-field-type game theory, developing advanced mathematical frameworks and
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, nonlinear optics, and the design, alignment, and optimization of optical setups. ● Experience with atomic force microscopy (AFM)-based infrared/vibrational spectroscopy or related nanoscale spectroscopy
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innovative solutions for future communication networks and sensing-enabled services. Job description The successful candidate will contribute to research on energy-efficient network design, optimization, and
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, optimization, and the experimental validation of communication-aware robotic systems. Position Requirements: Ph.D. in Robotics, Electrical Engineering, Telecommunications, Computer Engineering, Control
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Lehigh University Plasma Control Group (LU-PCG) and contribute to advanced control synthesis, neural observer development, scenario optimization, and AI-enabled digital twins for magnetically confined
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; design and optimize synthetic strategies for complex peptides, peptide libraries, and small proteins; develop scalable production methods using solid-phase peptide synthesis and native chemical ligation
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will closely interact with experts in microfluidics and bioinformatics, while spearheading the above project. Main duties and responsibilities include Optimization of single-cell sequencing workflows
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candidate will be expected to: Develop and optimize processes for the modification and nanostructuring of glass and optical material surfaces. Investigate relationships between fabrication parameters, surface