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for flexibility in the start and end dates, subject to approval by the department and the funding agencies. The successful candidate will join the Machine Learning & Data Science research group and conduct research
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, select, and apply standard techniques of routine research. Keep detailed records of data. Use computers and laboratory or technical equipment to perform data analysis, statistical analysis, and technical
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for this position have a great interest and knowledge in data analysis, filtering and modeling based on large amounts of data. It is important that you have a solid understanding of mining and mining systems to also
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Do you enjoy finding solutions to integrate and analyse large data sets of biodiversity dynamics and their drivers? Are you creative and able to couple various data flows and integrated modelling
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aims to use improved access to digital heritage to tutor the Digital Citizen in the use of big data. It brings together AI researchers and Digital Humanities scholars to seek solutions to the problem
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ideas and work together towards answering the big questions of the future. You also appreciate the exchange between disciplines, cultures and generations? We are looking for a/an University Assistant
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develop a body of high-quality publications in scholarly journals with global impact Proficiency in statistical software packages, including SPSS and R, for large and complex data analysis Proven knowledge
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, the deadliest malaria parasite species. Within UniGEM, the postdoc will be responsible for the simulation of synthetic data used to train, develop, and test the neural network. Scientific context: Malaria
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; familiarity with time series analysis and complex survey design and weighting is preferred. Experience in epidemiological data analysis of large datasets using R and/or STATA is highly preferred, competency in
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data and develop data-driven methods for predicting land loss and ecosystem transitions in wetland-rich landscapes of the Gulf Coast with a focus on coastal Louisiana. This candidate will directly