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Field
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platform, contribute to accelerating the realisation of PEDs? How can standards (e.g. in terms of data models and APIs) support this process, e.g. by streamlining data retrieval, integration and usage? How
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an oncolytic adenovirus, with the aim of assessing their predictive value. In addition, you will be involved in trial-associated studies that map immune responses to OV treatment in patients. Where to apply
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elaborate the timing of impacts, benefits, and risks of different CDR options. KEY TASKS: Mapping of intertemporal concerns of CDR activities, including emissions, removals, storage, risks, delays, and
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and sulfur) in high-temperature packed-bed reactors, including both Blast Furnaces and gas-based Direct Reduction shaft furnaces, and mapping their presence across gas, solid and condensed phases
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mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. In other words: there is plenty of room
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Python, C# (preferably across design-related APIs), and using Git. Experience developing plugins or toolsets within parametric modeling platforms like Rhino/Grasshopper, or similar. Knowledge of digital
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ecosystem mapping (e.g. remote sensing, GIS). You have affinity with renewable energy planning, nature-positive transitions, and/or biodiversity governance. You possess excellent analytical and writing skills
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traps, vegetation plots) and for ecosystem mapping (e.g. remote sensing, GIS). You have affinity with renewable energy planning, nature-positive transitions, and/or biodiversity governance. You possess
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multifidelity modelling, and goal-oriented numerical error estimation. The resulting surrogate model will map uncertain meta-ocean conditions to key quantities of interest for OFPV performance and sustainability
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mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. In other words: there is plenty of room