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mathematical models, validating them with experimental data, and making predictions. The ultimate goal is to decode the mechanisms behind intra-organelle coordination. Besides plant cells, such coordination is a
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, mitochondria, and chloroplasts. The project will involve developing mathematical models, validating them with experimental data, and making predictions. The ultimate goal is to decode the mechanisms behind intra
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that enhance the quality and efficiency of forest management planning. The PhD student will combine remote sensing with machine learning to detect cultural remains, predict terrain accessibility, identify
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responsibility is to conduct high-quality research on hybrid artificial intelligence. You will: Combine deep learning to capture long-term patterns and uncertainties with stochastic model predictive control
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evaluating designed backbones and predicting the functional effects of protein variants. In addition, the doctoral student will be part of the DDLS initiative, and participate in the DDLS Research School
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or predictive modelling of pathogen biology or host-microbe systems for which multidimensional, genome-scale experimental data are now available or it may use population-scale genetic, clinical, or public health
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prediction or patient stratification based on, among other things, molecular data. More information about the group’s activities can be found at: https://www.uu.se/en/department/immunology-genetics-and