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; Nguyen et al., 2023). By integrating large scale, multi-modal data and leveraging self-supervised and transfer learning, these models demonstrate satisfactory spatial-temporal simulation and predictions
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the framework of the ANR EmergeNS whose aim is to understand, through mathematical and computer models, the role that autocatalysis, multistability and spatial heterogeneity may have played in the emergence
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of ASICs dedicated to the readout of AC-LGAD (Alternating Current coupled Low-Gain Avalanche Diode) sensors, capable of very good timing (~30 ps) and spatial (~20 um) resolutions, which will be exploited by
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African research centres to enable independent analysis and local ownership of spatial data systems. The project’s research portfolio includes methodological innovation in geostatistical model development
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. Spectral dynamics of the conditional Lyapunov vector (https://www-cambridge-org.sheffield.idm.oclc.org/core/journals/journal-of-fluid-mechanics/article/spectral-dynamics-and-spatial-structures
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projects; knowledge of the English language. III. Work Plan: …………………………………………………………………………………………………………………. PT1 — Development and adjustment of specialized language models (LLMs) in the field of regional
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range and optical laser pulses, combining these with near-field methods for improved spatial resolution. To better understand our results, we develop simple theoretical models. The insights gained
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models. Expected Results: Ability to assess the influence of demise process on the release of emissions into different atmospheric layers. Numerical model to describe the temporal and spatial dispersion
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Your Job: In the CrowdING project, you will analyze experimental data from large crowds and develop quantitative measures to describe their spatial structure. To do this, you will use and expand
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relevant language) for ecological modelling, including the use of spatial datasets demonstrated ability to supervise or co-supervise Honours, Masters and/or PhD students Please refer to the Position