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to the space-based LISA observatory. The research will advance post-Newtonian waveform modelling through improved analytical techniques, incorporate strong-field information from numerical relativity simulations
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breeding. The project will involve extensive industry consultation therefore the ideal candidate will be possess strong communication, relationship-building, and analytical skills and be confident working in
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profound interest in inorganic chemistry, both in experimental and modelling applications. We are looking for candidates who are also interested in the analytical and numerical aspects of the work
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available. LISS DTP trains future research leaders to tackle global challenges through interdisciplinary collaboration, data-driven approaches, and impactful research. We welcome applications in any
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existing biomedical foundation models (e.g., Med-PaLM) using techniques like Low-Rank Adaptation (LoRA). Big Data Analytics: Managing and analysing complex, multi-modal data from globally significant
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Skills: Research-driven and self-motivated, with a strong passion for energy system related studies. Proficiency in English with strong communication and scientific writing skills. Competency in computer
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the research. They will conduct relevant systematic and/or meta-analytic reviews to describe the current literature and inform their research. They will undertake qualitative data collection and analysis and use
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marine sciences, biological oceanography, ecology, or computer sciences. Strong analytical, numerical and practical skills are essential. Experience in coding or applying quantitative methods in a
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. Robust evidence is needed to ensure the resilience of flood defences and maintain ecological health. For further information on the project, we will be hosting a ‘Prospective applicant webinar’ at 2:00pm
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data processing and nanoscale optoelectronics. This research is part of a UKRI Future Leaders Fellowship investigating “the hidden mysteries of light at the atomic scale”. The student will have