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Associate Professor (Independent Group Leader) in Data Science and Modelling of Whole-Cell Biosol...
) to in-field testing of up to 800 strains. The scale and standardized approach will create a unique foundation for advanced data analysis, including AI, machine learning, and statistical modeling, aimed
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, bioactive compounds, and other key nutrients. Develop and apply machine learning and modeling techniques to analyse, predict, and optimize the effects of processing on food composition, food Ingredient
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system management, especially around data quality, metadata governance, and the integration of machine data for long-term monitoring. Through a hybrid approach combining physical models and machine
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models, multi-trait approaches, or deep learning applied to genomics is particularly desirable. Experience with applications to complex diseases, especially cardiometabolic traits, is considered a strong
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at an international level developing deep learning, vision transformers, graph neural networks, foundation models, or related methodologies for integrating diverse imaging data with clinical, laboratory, and genomic
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environmental modelling, including data science methods such as AI and machine learning Proficiency in GIS and R programming or similar Effective communication skills and experience working with authorities
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, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer interaction