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of excellence for research and innovation, providing thought leadership, coordination and translation to impact across the quantum landscape in the UK and beyond. QuSIT builds upon a decade of government
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for chronic fuel cell monitoring in vivo including common electrochemical characterization methods. • Design and manufacture an micromachined interface between the fuel cell and the implantable
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will be tailored to your expertise, spanning from hardware design to system-level optimization and control methods. For the AI position, you will develop machine learning models that incorporate physical
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/experimental design and analysis of complex research data. Advanced knowledge of preclinical (in vitro and/or in vivo) validation. Excellent inter-personal skills with an ability to work co-operatively in a
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to develop knowledge and understanding to form relationships for future research collaboration. To plan and manage own research activity, research resources in collaboration with others and contribute
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(SPAD) detectors, we initiated and led collaborations to produce the first custom-designed InGaAs/InP single-photon avalanche diode detector (2006), first strained SiGe SPAD (2002), and custom-designed Ge
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of a Community of Impact Practice which will bring together community organisations, schools, health providers, and lived experience experts to co-design tools that help evaluate place-based mental
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(including mental health practitioners and teachers). You will contribute to the design or research materials and gather and analyse and present qualitative and quantitative data. You will promote public
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for future research collaboration. To plan and manage own research activity, research resources in collaboration with others and contribute to the planning of research projects. To deliver training in research
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. You will work with limited supervision to design and accurately execute experiments to achieve the goals of the project. Applicants should hold, or be close to completion of, PhD in Biology or a related