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new challenges and assignments. Education: The successful candidate will have completed a PhD in a relevant discipline such as hydrology, water resources, civil or agricultural engineering
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instrumentation or relevant radiogenic isotope analytical techniques. Demonstrated ability to interpret geochemical and isotope data, preferably with relevance to palaeoclimatic and paleoenvironmental
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completion), or equivalent PhD level qualifications. A PhD thesis topic in heavy-flavour hadron production is desirable High level analytical capability Ability to communicate complex information clearly
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microscopy) and biochemical analytical methodologies (e.g. micro-FTIR, micro-XRD, micro-MRI, micro-CT and so on) Bio-sample preparation Literature review, data analysis, writing reports and manuscript
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collaborative and interdisciplinary activities. Job Requirements: Preferably PhD degree in Computer Engineering, Computer Science, Applied Mathematics or equivalent. Strong academic background in machine learning
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preparation Literature review, data analysis, writing reports and manuscript Qualifications Candidates should preferably possess a relevant PhD degree, along with relevant research experience and high-quality
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qualifications. High level analytical capability in the area of electrophysiology and electromyography. Ability to communicate complex information clearly. Fluency in relevant models, techniques (e.g., TMS, EMG
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. The research will involve developing analytical models, performing large-scale numerical simulations of open quantum systems, investigating decoherence and noise processes, and exploring new architectures and
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handling, sterile formulation preparation, and physicochemical characterisation. Experience of using analytical tools and software relevant to formulation science, such as HPLC data analysis, spectroscopy
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to build ‘design-build-test-learn’ pipeline through computational design and experimental validation. About you PhD (or in the final stages of PhD submission) in computational biology, evolutionary genomics