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various components of the hydrological cycle (such as precipitation, evapotranspiration, runoff, and infiltration), forms the core of traditional hydrological modeling approaches. Although powerful
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Your Job: As part of an interdisciplinary team, you will develop approaches for the automated and large-scale provision and integration of energy systems data and models and apply data science
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Max Planck Institute for Demographic Research (MPIDR) | Rostock, Mecklenburg Vorpommern | Germany | about 11 hours ago
Institute for Demographic Research (MPIDR), in Germany, subject to MPIDR terms and conditions. The role is based within the Mortality and Inequalities Research Group at LSHTM with close partnership with
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Your Job: Develop AI pipelines that translate -omic signatures into dynamic model parameters Implement reinforcement-learning agents that optimise model performance Collaborate closely with
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of rural communities toward resilient, inclusive and climate-smart business models. The focus of this PhD will be on modelling and assessing the sustainability and macroeconomic implications
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integration of energy systems data and models and apply data science methods to make them usable for transparent energy systems analyses. The collected data will be processed and semantically enriched using
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with an increased risk of a number of age-related conditions including cardiovascular complications, immune-aging and myeloid premalignancies. Aging of HSC results not only from acquisition of cell
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Description Water can move in two interconnected realms: the fast, visible rivers at the surface and the slower, pressure-driven flow within substrates. Today, engineers can model each realm
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excursions. The PhD student will work on analysing the reliability of paleomagnetic records, deriving uncertainty estimates, and building time-dependent models of the paleomagnetic field evolution using a
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Virtual Training Environment (VTE) for disaster response simulation, integration of Building Information Modelling (BIM) with Structural Health Monitoring (SHM) using smart sensor networks, and resilience