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the project/work tasks: Advanced data management on large datasets to facilitate data for statistical analyses Design and plan analyses Make efficient analysis pipe-lines in the statistical software R
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to contribute to a world-leading project on Survey Data Collection Methodology Survey Futures https://surveyfutures.net/ . Survey Futures is a collaboration between nine universities and three survey
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techniques to enable large-scale data search across Personal Online Datastores (pods) hosted on distributed pod servers, addressing both keyword-based search and SPARQL querying. EPRESSO will build on and
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the direction of Dr Maslovskaya, you will be part of a large multi-institution team of survey data collection methods experts in the UK. You will analyse probability-based NatCen online panel data collected using
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School of Public Health i Boston with Associate Professor Jannicke Igland as local principal investigator at the University of Bergen About the project/work tasks: Advanced data management on large
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Missouri University of Science and Technology | Rolla, Missouri | United States | about 12 hours ago
Information Columbia offers small-town friendliness with big city features and a high quality of life for people of all ages and interests. Founded on education and known as an ideal college town, its location
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, translational research, and ultimately by influencing public policy and professional practice. We are seeking two Research Fellows in Epidemiology to work on the data analysis and paper writing of the Natsal
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of satellite data for monitoring inland and coastal water quality across Scotland. We anticipate that the successful candidate will spend around one third of their time on the Forth-ERA project. We are looking
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machine learning methods, particularly large language models (LLMs), to marketing research. Applicants are invited to contact Prof. Edward Lai at telephone number 2766 7141 or via email at edward-yh.lai
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to important public health topics. Studies will include descriptive epidemiology and use emulated target trial approaches for robust causal inference within large national health datasets. The post offers