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creating a unified data framework for microbial carbon dioxide conversion and establishing a predictive AI modeling. Your profile The candidate is required to have a strong background in AI/machine learning
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compositions. Initially, supervised learning models such as random forests, gradient boosting, and neural networks will be used to predict composition outcomes based on both literature scrapping and in-house
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, better adapted individuals can be selected at the seedling stage using only genetic data, accelerating the breeding cycle. Incorporating information about plasticity can aid genomic prediction modeling
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) Develop AI‑driven model calibration by designing a deep‑learning pipeline mapping data extracted from experiments onto force fields and use these predictions to initialise Cytosim simulations. (3) Use
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., SHAP, LIME) and radiomics preferred. Quantitative Analysis: Demonstrated ability to handle multimodal datasets, conduct statistical analysis, and apply predictive modeling and validation techniques
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of cementitious binders, including blended cements. Develop curing-specific DoC prediction models and validate against experimental results. Determine the effect of controlled exposure conditions on the DoC
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of emerging artificial intelligence (AI) applications and tools, with an interest in exploring their potential use in data analytics and predictive modeling. Ability to translate complex analytical concepts
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, mediators, and health outcomes, with the application to chronic diseases such as diabetes and its complications. AI and time series modeling for wearable device data and other longitudinal health data
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well as predictive models based on machine-learning technologies, in order to carry out code development and testing activities within the listed projects; therefore, skills in software design and development
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-ever Immune Digital Twin – a personalizable computer replica of the immune system – to enable everyone and anyone to assess and optimize the health of their immune system and simulate and predict its