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processing conditions. This will enable prediction of health benefits as well as sensory properties as taste and texture attributes. The main objectives of the PhD project are: To systematically characterise
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for variant effect prediction. Good knowledge of human prehistory and human evolution. Good knowledge of statistics. Training in bioinformatics, genomics, molecular genetics is advantageous. How to apply
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of various crop species, development of omics-based breeding tools, marker-aided selection, genomic prediction, and crossbreeding for crop improvement. More information about the department can be found
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Machine learning focuses on computational methods by which computer systems uses data to improve their own performance, understanding, and to make accurate predictions and has a close connection to
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of variation in protein structure and function, using simple measures such as overall hydrophobicity, in addition to modern protein structural prediction techniques. The student will then be responsible
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CH4 to the atmosphere, but future projections of river CO2 and CH4 emissions are lacking because we lack predictive models. Ongoing climate change is particularly severe at high latitudes and has
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to environmental shifts. This involves uncovering the key mechanisms that define bioregion boundaries and predicting their responses to a changing climate. To address these challenges, this PhD project will work
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represent the single most important carbon sink on the planet. An incomplete mechanistic understanding of carbon sequestration to wood limits our ability to predict the capacity of trees to assimilate CO2
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the development and application of theoretical mathematical models, with experimental data serving to validate the model predictions. Ultimately, the project seeks to decode this intricate cellular coordination