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document containing a CV, letter of interest, and a list of three (3) professional references is required to apply. Important Instructions: When prompted to upload your “resume”, upload your combined
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. Important Instructions: When prompted to upload your “resume”, upload your combined documents as one file. Please do not upload documents to “Cover Letter” or “References”. If the required application
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) professional references is required to apply. Important Instructions: When prompted to upload your “resume”, upload your combined documents as one file. Please do not upload documents to “Cover Letter” or
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Université Paris-Saclay GS Géosciences, climat, environnement et planètes | Gif sur Yvette, le de France | France | 3 days ago
. Ce projet, en collaboration entre l'Université d'Exeter et l'Université Paris-Saclay (LSCE), combine analyses observationnelles et modélisation océanique de pointe. Il se concentrera sur l'analyse de
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speech, as bridges to enhance cross-lingual transfer between high- and low-resource languages. The project combines resource creation with methodological research and aims to advance inclusive, robust, and
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semester Application deadline Will be announced on webpage: https://www.mgse.econ.uni-muenchen.de/application/index.html Tuition fees per semester in EUR None Combined Master's degree / PhD programme No
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; or equivalent combination of education and experience. Note: Some state job postings state you can qualify by an ‘equivalent combination of education and experience.’ If that language appears above, then you may
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Number: R145674 Clinical Research Assistant in the lab of Dr. Matthew Corriere Lab Website: https://u.osu.edu/corrierelab/ Functions as a Clinical Research Assistant providing support to Principal
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of employment. A retirement program with a generous employer contribution and additional voluntary retirement programs (457 or 403b) are available. https://www.kumc.edu/human-resources/benefits.html Employee Type
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approaches combining ab initio modeling, Raman vibrational spectroscopy, and machine learning for the study of electrode materials and their interfaces, with a focus on operando monitoring of full battery