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-term carbon cycle and over the coming century. This PDRA position will focus on model approaches to quantifying CO2 exchanges associated with chemical weathering associated with the warming cryosphere
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on and defensive mechanisms for safe multi-agent systems, powered by LLM and VLM models. Candidates should possess a PhD (or be near completion) in Machine Learning or a highly related discispline. You
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and glacier models, based on large ensembles of simulations extending to 2300. The simulations will be from two international projects aiming to inform the Intergovernmental Panel on Climate Change
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social media analysis, smartphone-based sensing, and agent-based modeling. Combining macro-level patterns with micro-level behavioral data, it will examine how polarized content influences stress, anxiety
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of the land ice contribution to sea level rise until 2300 with machine learning. You will develop probabilistic machine learning “emulators” of multiple ice sheet and glacier models, based on large ensembles
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(e.g., Reinforcement Learning, Agent Based Modelling) to join our team full-time as part of a large international collaboration of European researchers (incl. Tobias Dienlin, Veronica Kalmus, Adrian
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learning “emulators” of multiple ice sheet and glacier models, based on large ensembles of simulations extending to 2300. The simulations will be from two international projects aiming to inform
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. Desirable criteria Track record of interdisciplinary collaboration. Familiarity with cognitive architectures or agent-based modelling frameworks. Ability or potential to contribute to the development
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About us The Social Computation and Representation Lab (SoCR Lab; www.socrlab.net) uses mathematical models and causal experimental designs to understand the fundamental rules behind human and AI
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on evaluating the abilities of large language models (LLMs) of replicating results from the arXiv.org repository across computational sciences and engineering. You should have a PhD/DPhil (or be near completion