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The candidate will develop and benchmark zero-shot multimodal fusion models for rare disease prediction, using melanoma as a use case. The project integrates spatial and single-cell multi-omics data with
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-pulse laser micromachining facilities to develop crack-free laser texturing strategies for ceramic materials. Establish predictive models linking laser processing conditions to feature geometry and crack
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on temporal data (predictive maintenance, sensory processing for robot control, etc), in which efficient on-device processing is crucial. We are looking for a highly motivated PhD candidate with an interest in
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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