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for this scholarship you must: Have a first-class Honours degree in Computer Science or equivalent Have strong computational, programming, algorithms, and data analysis skills Provide evidence of adequate oral and
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humanities, digital health, computer science, information systems, user experience design) Have strong social research (quantitative/qualitative) AND/OR computing design and analysis skills Provide evidence of
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PhD Scholarship in Integrated Photonics for Telecommunication, Biosensing and Precision Measurements
propagation Interfacing to array microfluidics Image analysis of biosensor response Sensor surface biofunctionalisation Optical communications High-speed signal analysis Modelling of optical propagation in
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/focus groups) with industry, government and research bodies aimed at identifying systematic intervention; followed by an analysis of Product LCA to update, with the final research aim being to identify
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-institutional large scale human trial to address these vital questions. Co-supervised by Prof. Katie Flanagan and Dr. Jennifer Boer (bioinformatics analysis). The impact of PEG on vaccine efficacy and adverse
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analysis, particle analysis, electron microscopy, and synchrotron technology. The candidate should have experience in one or more of the following research areas: Mineral Processing, Chemistry, Chemical
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PhD Scholarship in ‘Using nanoparticles to enhance the immune response and improve vaccine efficacy’
sorting, multiplex cytokine analysis (Luminex), IVIS imaging, as well as ELISA, ELISPOT, immunohistology/immunofluorescence, proliferation and functional T cell assays. There is also potential scope to use
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foundational research skills, including experience in conducting systematic reviews, qualitative or mixed-methods research, and thematic analysis. Strong written and verbal communication skills are essential, as
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universities and industry organisations. More information can be found about the ARC on their website . Applicants are welcome to propose projects. Potential topics could encompass areas such as the following
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developing robust and feasible mathematical models for differential privacy by investigating the data dynamics (IID and Non-IID) of distributed machine learning. Besides, trustworthiness is another major