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Field
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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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of large multidimensional real world data sets using Stata, R, Python, or similar. Knowledge of C++ would be advantageous but not essential. Ability to communicate complex information clearly. Excellent
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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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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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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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Research Fellow in Intervention Development to join the Big Data in Health Group About us Our big data in health team at the University of Southampton is based in the Primary Care Research Centre
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to the applications of mathematics in cryptography, computing, business, and finance. PAP covers many areas of fundamental and applied physics, including quantum information, condensed matter physics, biophysics, and
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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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with time-series data. The role involves conducting research on multimodal learning and leading technical development efforts within the project. Qualifications Applicants should meet the following
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generally. Data sources for our work in this area are large-scale electronic health record data, medical claims data, mortality registries, and epidemiological cohort studies. The researcher will be expected