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in project meetings and team and lab meetings in Villefranche. The Laboratoire d'Océanographie de Villefranche (LOV ; http://lov.obs-vlfr.fr/ ) is located close to Nice, on the French Riviera. It
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-supervised learning, and few/zero-shot techniques — the student will adapt models to ecological data. Bayesian deep learning and ensemble methods will be explored for trustworthy uncertainty estimation
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and ocean alkalinity enhancement (OAE). The successful candidate will lead field, laboratory, and modeling studies that quantify the biogeochemical impacts of alkalinity addition in coastal ecosystems
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implementing models that integrate ecological dynamics, species traits, phylogenetic trees, and economic discounting; ● Devising Bayesian or POMDP frameworks to handle uncertainty about species interactions
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degree in plant or crop science, plant ecophysiology, agroecology, or related field. In this case, experience or a strong affinity for computational methods, like modelling, is required. Experience in
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, Evolution and Diversity, Environmental Sciences, Biodiversity, or a related field, with experience in freshwater fish ecology, taxonomic and functional diversity, statistical modeling in R, database
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performance under environmental stress. Training in geospatial analysis and ecological modelling will enable predictive insight into urban ecosystem dynamics. You will develop expertise in stakeholder
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Do you excel in numerical modelling to quantify hydrological processes and pollutant transport at catchment scale? In both research and science-based advice? Then apply to the open position as
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; Knowledge of stable isotope techniques and methodologies - information provided in the CV and/or in the motivation letter; Experience in data analysis and ecological modelling (GLM, GLMM and the like
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Bioacoustics: manage large-scale audio data; apply and refine automated call classifiers. Statistical ecology: use occupancy and relative-activity models that account for detection uncertainty. Remote sensing