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considerations in research involving human subjects. PREFERRED QUALIFICATIONS Expertise in epidemiological methods and study design. Experience with longitudinal data analysis and complex survey design
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the analysis, design, and implementation of complex systems. We focus on ensuring that our research results contribute to creating a better society by supporting areas such as health, green transition
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spectrometry and ion activation strategies (e.g. EID and photo-dissociation). The project will entail improving the current capability of glycoprotein structural analysis using bottom-up mass spectrometry
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skills in data analysis, machine learning, as well as in mathematical and computational modelling? You will have the opportunity to investigate innovative solutions using machine learning algorithms and
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after memory is established. ? Numerical analysis of complex data sets to evaluate the neural representation of information in the physiological recordings above. ? Collaboration
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CBS - Postdoctoral Position, Artificial Intelligence Applied to Metabolomics for Health Applications
-dimensionality and complexity of metabolomics data, requiring advanced AI/ML techniques for robust analysis and interpretation. Integration of multi-omics data (genomics, transcriptomics, proteomics, and
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statistical and spatial analysis. Skills in conceptualization, design, and production of complex data visualizations to clearly communicate analytic findings. Strong critical thinking, analytical, problem
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We are seeking a highly motivated person to conduct research in economic modelling of forest resources to support analysis of environmental and climate change issues. About the position The project
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chain network analysis and geospatial modeling. The successful candidate will have strong data science skills, including experience working with large, complex data from varied sources, and machine
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bioinformatics, and statistical modeling to decode the complex molecular mechanisms that shape human vision. By leveraging high-dimensional data and cutting-edge computational analyses, we aim to uncover