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Field
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the feasibility of applying a wide variety of scientific principles and theories. 4. Maintains substantial knowledge of state-of-the-art principles and theories. 5. Develops advanced analytical models and systems
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. Applications must be submitted online at https://workforum.memphis.edu/ and include a cover letter, CV, two representative publications showcasing your writing or analytical skills, and contact information (not
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work, designing rigorous analytical plans to test these hypotheses, lead the necessary data collection and analyses, writing manuscripts and grant applications, and presenting at local, national and
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opportunity to be part of large-scale experiments tackling pressing societal challenges. You'll be involved in every stage of the research process—from experimental design to data analysis and publication—while
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inorganic), nanocomposites as well as polymeric materials; Experience in the use of complex nanocomposite for tissue regeneration. Experience with a wide range of analytical characterization tools
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within our portfolio of hypothesis-generating screening studies, a methodological portfolio where we identify signals of interest from real-world register data to guide the conduct of tailored studies. We
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grid analytics, and scientific imaging. The successful candidate will design and implement sparse algorithms for large-scale scientific and numerical computations. This role offers an exceptional
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project, including experiment conception, preparation and setup, data collection, and data analysis and interpretation. Provide support to collaborative research efforts, including experiment design and
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Centre at University College Cork. The ideal candidate should be a quantitative, analytical researcher with a PhD in engineering, science, or economics, or a field related to energy, and a demonstrated
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purification and analytical techniques using NMR and Mass Spectrometry, and HPLC chiral separation. Analyze structure-activity relationships (SARs) and propose novel compounds and synthetic routes. Perform data