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shaping will be central to the study. The numerical model will be based on the boundary element method (BEM) and semi-analytical approaches developed at I2M. The experimental proof-of-concept will leverage
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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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of the control law. This will alleviate the modelling complexities and the online computational requirements of the control algorithms and provide them with learning, self-regulating and adaptive capabilities
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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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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 7 days ago
(Verhaeghe 2021); or even functional test migrations (Hlad and Verhaeghe 2025). Challenges The objective of this thesis is to extract and model the control and data flows observed during the execution of a
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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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, 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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, 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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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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, materials science, or a closely related discipline Apply: https://mgician.eu/research/doctoral-candidate-projects/dc1/ DC2: Synthesis and Transport Studies of Magnesium-Based Thermoelectric Materials Host