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collaborative research environment at UiA focused on robust inference about ecological and evolutionary change in human-influenced systems. Researchers work with complex data from diverse marine and terrestrial
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altimetry (ICESat-2, CryoSat-2, SWOT and forthcoming CRISTAL) missions, supported by meteorological data, climate reanalysis and in-situ observations. The project will focus on case studies from Arctic
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laboratory work, bioinformatic processing of Next Generation Sequencing data, and population genomic analyses, including demographic inference. The purpose of the fellowship is research training leading
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applicants with a strong background in machine learning and statistics, who are eager to contribute to cutting-edge methods for generating private and fair synthetic data with good utility. This project
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reviews, policy analysis, interviews, focus groups and other qualitative research methods. The candidate will examine questions such as how comfortable people are with their health data being used to create
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. Relevant projects may make use of large-scale survey data, administrative or register-based data, repeated cross-sectional or longitudinal designs, evaluation studies, or combinations of these. Applicants
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, durability, and structural testing of cement-based materials is an advantage experience with data processing and analysis of material or structural response is desirable Personal qualities strong ability