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that model the complex space of ingredients and their properties can be immensely useful. These representation spaces can be informed by multiple modalities of data, spanning time-series data, microscopy
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motivated candidate with a background in neuropsychology, medicine, neuroscience, molecular biology, biostatistics, pharmacology, pharmacoepidemiology, public health, statistics or a related field. The
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, or related Experience and skills · Multi- and hyperspectral images processing · Knowledge of quantitative remote sensing · Knowledge of physical and statistical modelling concepts
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the project, you will: Actively participate in group meetings, design statistical analysis plans in collaboration with other researchers, perform data analyses, write scientific articles, supervise
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research in the current age lies in joining forces from multiple disciplines to focus on understanding causal and mechanistic links between the microbiome and chronic diseases alongside generalisable
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would be doing: Process and analyse large-scale calcium imaging datasets from multisensory experiments, including neural responses from visual and auditory cortices recorded over multiple days Apply and
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from multiple sources to estimate air quality, along with associated measures of uncertainty. Some traditional models can be relatively restrictive in nature and lack capabilities to deal with large
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epidemiology, causal inference, genetic epidemiology, and machine learning. As a PhD candidate in the project, you will: Actively participate in group meetings, design statistical analysis plans in collaboration
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application-oriented research that unlocks the potential of data through rigorous analysis – advancing solutions in societally relevant domains. Your profile Master’s degree in Statistics, Industrial
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and range shifts from mountains worldwide Participate in the development and adaptation of statistical models for analyzing the relationship between species distributions and climate Collaborate closely