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. Drawing on insights from hydrology and quantitative risk management, the project will also develop improved methods to identify energy droughts and detect "worst-case" weather years for energy security
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concentration in specialized clinics with access innovative treatments and technologies, such as (hybrid) surgical equipment, cell therapies, AI-driven methods, and advanced genomics. The project will focus
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of numerical, empirical, and theoretical techniques, with a special focus on decarbonization of the industry and energy sector in the EU and The Netherlands. The PhD position is embedded in the Centre
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- and knockoff-based methods that allow for relatively model-free inference. In this project, we aim to combine the strengths of these three frameworks into a novel and coherent whole. The project is
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between these important climate subsystems, using models of different complexity and a combination of mathematical, numerical and data analysis methods. You can find the other vacancy at PhD Position in
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, efficient, and adaptive energy infrastructures at local level. By leveraging data-driven methods, cities can devise strategies that balance energy supply and demand, improve electricity grid flexibility, and
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gradient that determines atmospheric water transport to extra-tropical regions. To this end, you will generate proxy data to assess temperature, hydrology and carbon cycle information. Methods might include
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Apply now The Faculty of Science and the Leiden Institute of Advanced Computer Science (LIACS) are looking for a: PhD Candidate in AI for Network Analysis (1.0 FTE, 4 years) About this position
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, climate sciences, mathematics, or geo-information science or a similar relevant field, and are you proficient in programming with R/Python? Then we have the perfect opportunity for you! The Team
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authority. 2021: Nadine Akkerman Her publications on women's history, diplomacy and espionage in the early modern period are read by a wide audience and she uses innovative methods for her research. Nadine