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that is production-ready for dissemination to other laboratories and for diagnostic use, and the management of large-scale data. They will join a team of computational and experimental postdoctoral fellows
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by Asthma + Lung UK and is an exciting opportunity to work on a project that is a priority area for them. The successful applicant will be leveraging their data science expertise to work on a complex
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opens for a large amount of novel research within statistical data analysis, ranging from genetic epidemiology to statistical methods development. Research environment: The candidate will have a close
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Fritz Haber Institute of the Max Planck Society, Berlin | Berlin, Berlin | Germany | about 6 hours ago
mechanics, data-driven approaches, and machine-learned interatomic potentials are highly beneficial but not required. We offer The 3-year Liebig PhD Fellowship is tax-free and is funded 1850 euros/month. The
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on the project “Out of Cycle Next Generation Highly Efficient Air Transport (ONEheart)”. The project is a large, national effort led by Airbus Operations Ltd with several industrial and academic partners. The aim
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opportunity CSIRO has collected large amounts of valuable environmental DNA (eDNA) data and now has the chance to use this data to transform how we observe and protect marine ecosystems. Towards this end, CSIRO
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review, law and policy analysis, secondary data analysis, key informant interviews and participatory Photovoice and Q Study workshops. The role holder will work with the Project Lead, Dr Lauren Eglen, and
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Asia, towards safer and more sustainable societies. For more information on EOS please visit http://www.earthobservatory.sg. The Earth Observatory of Singapore (EOS) seeks a Research Fellow to work
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biological processes by developing theory, innovative modeling tools for large-scale biophysical simulations, and computational frameworks for analyzing increasingly large and complex experimental datasets
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be research, data analysis, drafting and publishing research articles, and other scholarly outcomes that arise from a four-year project that uses temporal embeddings of large, heterogeneous scientific