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-IMPACT ( TURBOmachinery Innovative Manufacturing, Processing, Analysis, Characterization, and Topology; Website: https://cordis.europa.eu/project/id/101311350 ). The TURBO-IMPACT project, funded by
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together with other energy assets, such as electrical boilers, within a Model Predictive Control (MPC) framework that optimally balances electricity and heat production. Within FLEX-SMR, this PhD focuses
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support adaptive and automated process execution.• Extending BPM models, notations, methods, and technologies to enable sustainability-driven decision-making.• Evaluating and validating proposed solutions
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. The research will involve training machine-learning models on large structure and sequence datasets and integrating membrane-specific biophysical constraints to enable the design of membrane proteins and
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more reliable designs. The student will use advanced numerical simulations at KU Leuven to model the impact of large waves on OFPV structures, capturing key processes such as wave breaking, overtopping
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deploying the face de‑identification pipeline on resource‑constrained hardware, optimizing the underlying AI models based on latency, memory, and power constraints, and building demonstrators that showcase
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BAP-2026-449 Is the Job related to staff position within a Research Infrastructure? No Offer Description In industry, language models are currently being widely experimented with to build, among other
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of a locally calibrated fire spread model that accounts for land management and design scenarios (PhD 1) - the generation of near-real-time, high-resolution maps of fuel loads, fuel moisture
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the use of (multi‑modal) Large Language Models (LLMs) and other AI techniques to support the automated generation and adaptation of DWIs from DPP data. This research will explicitly assess which types
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-constrained devices such as wearables, smart sensors, hearables, and IoT nodes. While current deployment methodologies can optimize models before deployment, the resulting software remains static throughout