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, technology development, and science. On the local education campus, various university and non-university research and development institutions are working together in a unique collaboration and a state-of-the
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PhD scholarship in Mid-Infrared Frequency Comb Technology for High-Sensitivity Sensing – DTU Electro
-sensitivity sensing applications. Your responsibilities will follow the project scope described above and include laser design and development, nonlinear frequency conversion, frequency-comb stabilization and
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). The successful PhD candidate will use a combination of adaptive laboratory evolution and rational metabolic engineering to achieve these goals. In addition, they will develop growth‑coupled selection strategies
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Robotics Centre (MRC) at The Chinese University of Hong Kong (CUHK). The successful candidate will contribute to the development of an advanced telesurgery platform built on a novel surgical system. This
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PhD Studentship: Building Brain Circuits: decoding RNA processing in the developing mammalian cortex
The mammalian cerebral cortex contains a wide diversity of neuronal cell types that form highly specific connections during postnatal development to support complex behaviour. A major emerging
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morbidity and mortality. Understanding the mechanism that drives the progression of MGUS to myeloma is therefore key in preventing development of this incurable cancer. Changes in both the adaptive and innate
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for the chemical industry. By enabling the direct production of formate / formaldehyde from carbon-based feedstocks using renewable electricity, the project contributes to the development of sustainable chemical
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studies; conducting high-quality empirical research (e.g., archival research and cultural analysis; contributing to the development of a theory of the queer intellectual in close collaboration with
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, stiffness loss, damage evolution, and transient creep interact under coupled loading. The project will develop temperature-dependent constitutive models informed by numerical simulation. Machine learning
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, the project will establish predictive frameworks capable of optimising process parameters, controlling microstructure evolution, and improving part quality in real time. Robotic platforms will be used