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biological approaches, with the objective of identifying optimal pathways for resource recovery. The project will also focus on the combined treatment of phosphogypsum and brines, studying the synergistic and
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researcher will test these materials to design, fabricate and optimize organic optoelectronic devices, focusing on the manufacturing aspects including miniaturisation of devices, encapsulation, flexibility and
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systems. Application areas include hot-spot cooling, energy harvesting for IoT devices, and sensorics. Main tasks: Design, synthesis, and optimization of thermoelectric thin films (n- and p-type
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week/ 50 %), initially limited to two years with possibility of continued employment. The successful candidate will be involved in operating, maintaining, and optimizing high-end imaging and spatial
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-oriented problems involving optimization, artificial intelligence, workflow redesign, and stochastic assembly line balancing. The position will involve close collaboration with industry partners
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developing learning-based perceptive approaches. You will develop learning and/or optimization based approaches to multi-robot path and motion planning and coordination, integrating multi-modal perception and
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scale. Key activities include: • Fracture mechanics and fatigue for bio-based composites • Numerical implementation and optimization. • Model calibration and validation. • Prototype deployment and testing
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paradigms, including continuous aperture MIMO, pre-optimized MIMO arrays, flexible intelligent metasurfaces, and tri-hybrid MIMO systems, with a particular emphasis on near-field propagation regimes relevant
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multiplex and multilayer networks alongside with the observed links in order to predict or reconstruct the missing links. The first step is to explore different optimization methods using low rank tensor
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 7 days ago
, energy optimization, and sustainable urban mobility. The position focuses on the development of a hybrid electromobility model within the eMob-Twin platform, combining large-scale mobility data from