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characterization, distribution, diversity, and transmission mechanisms between rhizobia and hostel plants. Main responsibilities: The selected candidate will be expected to: Conduct research as part of the project
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solutions for sustainable management of water at the farm-scale. Our goal is to create a scalable and cost-effective distributed water capture and storage solution that minimizes evaporation where we will use
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learning (RL) and deep reinforcement learning (DRL) for autonomous process management, dynamic resource distribution, and real-time decision-making. Design and deploy digital twins for integrated chemical
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scenarios including non-iidness of data distribution, system heterogeneity, and dynamic environments. Key duties: The Postdoctoral Fellow is expected to: Publish in high-impact journals in the field
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Diffraction (XRD) and Rietveld refinement for phase analysis. Electron microscopy (SEM, TEM, EDS) for morphology and elemental distribution. Spectroscopic techniques (XPS, Raman, FTIR) for surface chemistry
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distribution. Spectroscopic techniques (XPS, Raman, FTIR) for surface chemistry studies. Electrochemical Performance Evaluation: Galvanostatic cycling to assess capacity retention and rate capability
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communication resources to train the federated machine learning model efficiently. She/he will investigate realistic scenarios including non-iidness of data distribution, system heterogeneity, and dynamic