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predictive control of carbon mineralisation through high-throughput mineralogy and machine learning.” This is an exciting opportunity to contribute to innovative research at the interface of mineralogy
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 8 days ago
the prediction of vehicle flows, energy demand, and flexibility of electric vehicle fleets, with applications to energy and transportation systems. The work lies at the intersection of systems and control, data
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(e.g., AI-assisted workflows, ontology-backed reasoning, requirements co-pilots) into the sandbox. Ensure the sandbox supports controlled experimentation and repeatable demonstrations of SE capabilities
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but not limited to: o Quantum error correction, fault tolerance, and resource optimization. o Entanglement dynamics, quantum control protocols, and hybrid quantum-classical algorithms. o Modeling and
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architectures to solve data-driven sensing and control problems related to turbulent atmospheric flows. The work will center around investigation of reinforcement learning and convolutional neural networks
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facilities to conduct world-leading fundamental and applied research within communication, networks, control systems, AI, sound, cyber security, and robotics. The department plays an active role in
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: - Development of programmable control elements for self-amplifying RNA (saRNA) therapeutics. - Regular mentorship meetings with the supervisor - Training in the new technique and workflows relevant
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of experiments or projects under control or supervisory responsibility. 2. Recommends changes in research, testing or experimental procedures. 3. May be responsible for a single highly technical and complex piece
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Job related to staff position within a Research Infrastructure? No Offer Description Area of specialization: Agronomy, Greenhouse gas measurement, Controlled and field experiments monitoring. About UM6P
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The research goal of PCF is to understand and to control liquids and their interfaces from molecular to macroscopic scales. Our research connects fundamental phenomena in static and dynamic wetting, nanofluidics