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Inverse Methods and Ionospheric Modelling Research Fellow - School of Engineering - 106995 - Grade 7
Job Description Position Details College of Engineering and Physical Sciences Location: University of Birmingham, Edgbaston, Birmingham UK Full time starting salary is normally in the range £36,636
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expertise in ultrafast spectroscopy. Ideal candidates will have completed a Ph.D. in chemistry, physics, chemical engineering, or materials science/engineering by or before August 2026. The candidate must
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USDA-ARS Molecular Biology Postdoctoral Fellowship in the Natural Products Utilization Research Unit
. This fellowship aims to improve crop protection from pests through the use of natural products, either by discovering safer natural pesticides or by manipulating their production in plants by genetic engineering or
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code LISBOA2030-FEDER-00819600 at the Funds Counter, funded by the Lisbon Regional Programme, FEDER component, and by the Foundation for Science and Technology, I.P. through national funds (PIDDAC
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head an independent research team dedicated to unravelling the basic mechanisms of the regenerative process, enabling the next generation of discoveries to prevent, halt, and reverse damage from disease
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. Must be able to work at a computer for extended periods for data analysis, and manuscript preparation. May require routine work with biological samples, including recombinant proteins and antibodies. Use
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EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Organisation: Cranfield University Faculty or Department: Faculty of Engineering and Applied
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approaches (e.g., using R, NetLogo, or similar) Working knowledge of ecological (especially landscape ecology) research methodology and biostatistics Computer proficiency, including use of statistical software
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coordination meetings. The Centers for Disease Control and Prevention (CDC) is one of the major operation components of the Department of Health and Human Services. CDC protects America from health, safety and
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efficient Artificial Intelligence (AI) framework for accelerated discoveries in surface science and catalysis, transforming the scientific discovery process into an adaptive, autonomous, and self-improving