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management system (EMS) Developing a procedure for local manufacture of electrolyte Analysis and publication of data from the installed battery The successful candidate will work in collaboration with SOLead
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data and a large battery of questionnaires. Because of the quality of the datasets, the elevated risk of children involved and the importance of the research questions, we anticipate submission of a
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Australian National University | Canberra, Australian Capital Territory | Australia | about 18 hours ago
Position is an equal employment opportunity measure aiming to increase representation by the target group in accordance with the University Identified Positions Procedure For further information please
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for conducting quantitative data analysis of large secondary datasets and be based at the University of Bristol. There are opportunities to work on several other ongoing and upcoming research projects to help
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, economics, geography, psychology, computer science or related field and some experience with environmental data and large data sets. Due to requirements of the funding source, must be a U.S. Citizen or U.S
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will develop, implement, and apply advanced computational tools and reproducible workflows to interrogate large-scale, liquid chromatography–mass spectrometry (LC–MS)-based comparative metabolomics
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apply the Helsinki Discrete Element Model (HiDEM) to simulations of brittle-elastic fracture, calving and retreat at Kangerlussuaq Gletsjer (KG), a large outlet glacier of the Greenland Ice Sheet. Working
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interdisciplinary team at the Technische Universität Dresden, focusing on the integration of multi-omics data to better understand, diagnose, and treat metabolic diseases (i.e. obesity, diabetes, metabolic
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 8 days ago
, training, mentoring & upskilling opportunities. For more information on a range of lifestyle, financial and non-financial rewards and programs, please click here . To see what the Science and Medicine at ANU
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of patients. The candidate will contribute broadly to the project to enable the development of new algorithms for clinical AI based on patient data from heterogeneous sources, notably language/speech-based