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in ecology and evolution, as it underpins our ability to predict species’ responses to climate change and human pressures. Palms are very abundant and often hyperdominant in Amazonian forests, making
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to compare theoretical predictions with experimental observations and measurements. - extend existing stochastic models and develop new models to understand actin dynamics in different contexts
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power of NNs with the ability of LMMs to robustly learn from structured and noisy (non i.i.d.) data, applying them on the prediction of both plants and human phenotypes. These models will combine
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elements are frequently involved in horizontal transfers, allowing them to colonize new hosts. However, understanding and predicting how horizontal transfers shape the distribution of TEs among species is
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predictive modelling Public policy evaluation Management and analysis of survey data Software proficiency Statistical and econometric packages such as Stata, R, or Python GIS software (QGIS, ArcGIS
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 24 days ago
extracted today with in-operando experiments (e.g. tomography). AIM's interdisciplinary methodology bridges applied mathematics, mechanics, and artificial intelligence to better understand, model, and predict
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Inria, the French national research institute for the digital sciences | France | about 2 months ago
to predict memory accesses and anticipate page faults. At present, it is almost impossible to execute AI models in kernel space, since floating-point operations—required by AI workloads—are not supported
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to the specification and analysis of data from major space missions (SMOS, Biomass, Venµs, Trishna) and develops models capable of describing and predicting the evolution of continental surfaces under various pressures
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, that could be employed to predict degradation in a machine operating under real-world conditions (electrical, thermal, mechanical stresses, humidity, pressure, etc.). • task 3: this task consists in
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well as investigating the role of non-local correlations in the quantitative prediction of satellites positions and pole strengths. The successful candidate will participate in numerical research and scientific code