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Faculdade de Ciências Médicas|NOVA Medical School da Universidade NOVA de Lisboa. | Portugal | 1 day ago
supervision of the project’s Principal Investigators: Create a spectra library of arginine methylation peptides Train transformer models to predict MSMS spectra of arginine methylation peptides. Place of work
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and proven expertise in leading predictive modeling, data warehousing, and the deployment of self-service reporting tools and dashboards. 5+ years of senior-level management experience leading large
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planned acts, such as targeted terrorist activities. This exciting project will focus on developing a mathematical model (and a supporting research software) to predict the key performance indicators of a
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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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., 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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) 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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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