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. Qualification requirements The selected candidate should have a master’s degree in a related field: e.g., civil engineering , mechanical engineering , computational materials science , or applied mathematics
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About us The Faculty of Natural, Mathematical & Engineering Sciences (NMES) comprises Chemistry, Engineering, Informatics, Mathematics, and Physics – all departments highly rated in research
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Laboratory in the `Digital Innovation Facility¿ at the University of Liverpool. You will possess, or be close to completing, a PhD in Electrical Engineering / Electronics / Computer Science or a relevant
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desire to learn others: molecular biology, C. elegans or other model organism research, confocal imaging, computational analysis, preferably in python and electrophysiology. We are also looking for someone
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development. The ideal candidate will have a PhD in a relevant biological subject, together with experience in molecular biology, cell biology and immunology. Familiarity with flow cytometry, vascular biology
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development. The ideal candidate will have a PhD in a relevant biological subject, together with experience in molecular biology, cell biology and immunology. Familiarity with flow cytometry, vascular biology
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individual on an upward trajectory and will fully support applications for independent fellowships to follow this initial post. Applicants should hold a PhD (or equivalent) involving neuroimaging, cognitive
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Postdoctoral Researcher in Machine Learning of Isomerization in Porous Molecular Framework Materials
broad range of applications. Computational chemistry and Machine Learning increasingly underlies MFM research to search or screen candidate MFMs prior to synthesis. A major drawback when applying
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base, the partnership will bring together the University of Oxford’s expertise in statistics, mathematics, engineering and AI with industry scientists. Within the partnership, small research teams will
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and science exploitation of the MIGHTEE survey data. The postholder would have the opportunity to identify new discoveries in the data and would be ideally placed to lead the science based on the data