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infrastructure to support predictive analytics, recommendation, and dynamic pricing. Create pipelines and databases capable of aggregating and organizing information from multiple heterogeneous sources. O5
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ultimately seeks to predict how species respond to different sources of predation in the context of ongoing environmental changes, in order to better adapt monitoring tools and hunting quotas
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hydrogenation, dehydrogenation, and hydrogen transfer reactions. Detailed characterization and kinetic studies will be performed to test computational predictions and microkinetic models, and to refine machine
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perturbations. The numerical predictions will be systematically compared with available experimental data from IRPHE to assess accuracy and refine the model, ultimately leading to a validated numerical tool
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identification, i.e. learning of models from measured data, and iii) real-time control, e.g. using the model predictive approach. We are working on several projects with industrial partners across the energy
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these challenges by advancing sensitivity-based modelling, fluid–structure interaction (FSI) methods, inverse problem solving, and surrogate modeling techniques, ultimately enabling predictive, adaptive, and
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. The researcher will develop novel research that applies advanced data science, machine learning and deep learning to various different data modalities. An ambition of this team is to implement predictive modelling
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 29 days ago
learning models for antimicrobial activity prediction (e.g., Weka); - Strong communication skills; - Fluency in English (written and spoken). The candidate must demonstrate interest in microbiology and
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and increased uncertainty in life and non-life insurance modelling. data-driven prediction of insurance premiums and associated quantification of uncertainty. Qualifications and personal qualities
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experiments to build demographic models that quantify the population-level impacts of maladaptation. Second, they will use common garden data to link fitness consequences with predictions from landscape genomic