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PhD Studentship: Advancing solid-state battery electrolyte manufacturing with terahertz spectroscopy
develop terahertz spectroscopy to advance materials insight and quality control for next-generation energy technologies. The project: Solid-state electrolytes are attracting growing interest for next
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system?” The project will begin with the design and construction of a simple benchtop experimental phantom in which fluid volume can be altered in a controlled and independently measurable manner. Purpose
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with applications to quantum sensing, computing and communications. Topics will include: Sequential and universal inference: adaptive measurement and stopping rules controlling type-I error with finite
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their website at https://www.naritalab.com/ Our laboratory investigates the biology of preneoplastic cell states, with particular interest in how changes in cell functional identity and plasticity are controlled
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evolution in Miscanthus hybrids, and to investigate how regulatory, epigenetic, and structural mechanisms contribute to the balance or dominance among subgenomes. Miscanthus is a notable bioenergy crop
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the work aligns with your goals and aspirations. For more details see https://binyshlab.com/positions/ What will you do? Conventional robotic bodies rely on computationally intensive centralized control and
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defects and remain a leading cause of infant morbidity and mortality. Despite their clinical importance, the molecular mechanisms controlling development of the aortic arch arteries, which give rise
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defects and remain a leading cause of infant morbidity and mortality. Despite their clinical importance, the molecular mechanisms controlling development of the aortic arch arteries, which give rise
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slowly, or act quickly but lack robust planning. Frontier models typically depend on heavy compute, cloud inference or controlled settings, limiting real-world use under compute, latency and energy
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on information theory, machine learning, and control to analyse how local variability, sensor drift, and platform differences affect both global model performance and human supervisory factors such as workload and