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candidate will lead advanced statistical analyses integrating ecological datasets with spatiotemporal modelling frameworks. The work will contribute with evidence-based data to development of ecosystem-based
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, or at a specific controlled test-site such as NLR’s (MITC) “DigiCity” urban city mock-up initiative, or a similar initiative near Schiphol Airport. As for the subjective comparison, VR experiences based
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, and machine learning models for functional genomics research in mycobacteria. Responsibilities Responsibilities include: Develop and maintain Django-based web applications and databases for sharing
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-based techniques (e.g., deep neural networks) will be used to automatically learn the system dynamics and the modelling errors, as well as to obtain an automatic tuning of the cost parameters/constraints
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solutions for vibration and noise control in lightweight structures (https://cordis.europa.eu/project/id/101227712 ). The project focuses on the development of Acoustic Black Hole (ABH) technologies
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behaviours of multi-agent systems in response to changing internal states and external environmental conditions. Both traditional model-based approaches and modern learning-based control techniques will be
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predictive control, optimization-based decision frameworks, and data-driven performance modelling. The overall goal is to develop computational methods that enable efficient and intelligent operation of wind
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theory, modeling, and AI-assisted optimization activities within the consortium. Reporting and dissemination of the results. Share this opening! Use the following URL: https://jobs.icfo.eu/?detail=1074
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of Research ExperienceMore than 10 Additional Information Benefits Work in a dynamic group. Eligibility criteria Good command of English. Knowledge in project field. Selection process Please see https
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involved in reproduction. The objectives are to define an experimental model to identify the constraints of sexual selection and to control the parameters for optimizing insect rearing. The thesis's purpose