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well as key skills development. Target Group particularly gifted German and international doctoral candidates from any discipline completing promising doctoral dissertations at a German higher education
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. You will be part of a team pursuing the development of novel integrated data analysis diagnostic tools that address key challenges in the field of energetic particle physics in fusion plasmas, such as
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mechanisms governing the formation and function of the testis, production and function of sperm, fertilisation, as well as early embryonic development – in both health and disease. To this end, we combine
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are eager to contribute to this rapidly developing field. Our research spans multiple disciplines, and we welcome applicants with backgrounds or interests in areas such as quantum optics, nanofabrication
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, such links have predominantly been directly from a wind farm to shore (point-to-point). However, proposals are developing for multi-terminal grids for improved reliability and asset utilisation. Proposals
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of therapeutic cells or biomolecular cargo, and We further propose that by understanding and tuning the fluorescence mechanisms of C-dots, we can develop reliable nanosensors for real-time bioanalytical readouts
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-time imaging. This PhD project aims to address these barriers by developing AI-driven methods for fluorescence fluctuation super-resolution microscopy (FF-SRM), with a particular focus on the emerging
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polymer insulation fails above 200–280 °C, limiting motor performance. Our project objective is to develop durable ceramic coatings via sputtering on metal hairpin windings, raising possible operating
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supported by the Ministry of Defence and EPSRC for building the necessary expertise to develop next-generation hypersonic vehicles. This offers a fully funded 4 years stipend and tuition fees at the Home
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
, this project contributes to advancing smart materials diagnostics, supporting sustainability, safety, and technological competitiveness in key engineering sectors. To develop an AI-driven methodology