47 algorithm-development-"UCL" PhD scholarships at University of Groningen in Netherlands
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flavour violating decays of b hadrons with data collected by the LHCb experiment at CERN. In addition, the successful candidate will contribute to the development of the next upgrade of the readout system
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experiment at CERN. In addition, the successful candidate will contribute to the development of the next upgrade of the readout system and thus to preparing the LHCb experiment for future data taking
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infrastructure managers in developing cross-sectoral strategies to proactively shape infrastructure demand, as an alternative to the traditional and increasingly untenable 'predict-and-provide' paradigm. By
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internationally recognized research centre and gain valuable research experience at a top-ranked European university. As a PhD candidate, you will develop your own research project in consultation with
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candidate, you will develop your own research project in consultation with the supervisory team. You will conduct independent and original academic research and report results via peer-reviewed publications
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Organisation Job description Topic of research: Development of sustainable ZnAlMg-X alloy coating for green steel applications ZnAlMg alloys coated steel belong to the most important materials
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fail to reach those most in need. To develop equitable and effective policy tools, further research is needed on the contexts, compositions, and mechanisms of retrofits, as well as a deeper understanding
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Engineering, University of Groningen. The research is aimed at the development of novel methods for nanomedicine characterization and to study their interaction with cells (e.g. uptake, intracellular
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transition. International research echoes this concern, noting that retrofit programs frequently fail to reach those most in need. To develop equitable and effective policy tools, further research is needed
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and foster equitable decision-making? To answer this question, the research will explore areas such as the following: Characterizing human-AI collaboration for bias mitigation – Developing a conceptual