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Field
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interested in how floods are generated and which processes can lead to floods? Do you want to understand how extreme events manifest and how they differ in space and time? Do you want combine statistical and
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come from one of the following countries: https://www.ugent.be/nl/onderzoek/financiering/bof/dos/countrylist.pdf More information about the scholarship: https://www.ugent.be/en/research/funding/bof/dos
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and statistics in a higher education institution in Romania Specific Requirements advanced knowledge of econometrics and programming in Gauss and/or Matlab and/or Python and/or R is an advantage
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Mathematical Statistics: https://www.umu.se/en/department-of-mathematics-and-mathematical-statistics/ We look forward to receiving your application!
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opportunity to be part of the project “Bavarian Artificial Intelligence for Insect Monitoring” (https://go.ur.de/baimo ), which investigates the effects of climate change on insect populations as part of
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opportunity to be part of the BaySensAI project (https://go.ur.de/baysenseai ) and develop an AI-based prediction and monitoring system for biodiversity data as part of the Bavarian research network bayklif2
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project work plan and milestones Your profile Completed university studies (Master/Diploma) in the field of Chemical/Metallurgical/(Mineral) Process Engineering, Data Science, Statistics, Machine Learning
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for coastal ecosystems. You will perform statistical analyses of time series and spatial data on ecosystems and human activities and participate in more holistic analyses of socio-ecosystems. You will also
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issues in federated and decentralized learning systems. The aim is to develop novel methods for securing communication against passive and active adversaries, leveraging tools from statistical estimation
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emerging treatments for people living with multiple long-term conditions. This project will utilise the SAIL Databank’s (https://saildatabank.com/ ) rich anonymised population-scale, individual-level, linked