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mathematical modeling and programming. * Research experience and publications in machine learning, complex networks, and mathematical modeling. * Excellent English communication skills (written and oral
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31 Oct 2025 Job Information Organisation/Company FAPESP - São Paulo Research Foundation Research Field Engineering Researcher Profile Established Researcher (R3) Country Brazil Application Deadline 21 Nov 2025 - 23:59 (UTC) Type of Contract To be defined Job Status Not Applicable Is the job...
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) and hosted at the Institute of Energy and Environment (IEE-USP). Applicants must have experience in atmospheric numerical modeling, climate data analysis, and extreme events. Applications must include
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staff position within a Research Infrastructure? No Offer Description Opportunity code: Postdoctoral (RL2_SP3_WP3.6) Area/Theme: “Thermo-Fluid Dynamic Models and Flow Assurance / Optimization
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) of Hospital das Clínicas (HC), the hospital complex run by the University of São Paulo's Medical School (FM-USP) in Brazil. A better understanding of the complex interactions involved has the potential
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staff position within a Research Infrastructure? No Offer Description The Stochastic Systems Modeling project in São Paulo state, Brazil, is recruiting one post-doctoral fellow in the fields
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staff position within a Research Infrastructure? No Offer Description The Stochastic Systems Modeling project in São Paulo state, Brazil, is recruiting one post-doctoral fellow in the fields
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staff position within a Research Infrastructure? No Offer Description This post-doctoral position aims to model two enhanced recovery methods simultaneously: CO2-WAG and the designed water (or calibrated
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validate the predictions of the ML models by means of atomistic modeling, in particular density functional theory (DFT) calculations, obtaining simulated electronic and emission spectra for the CDs. Finally
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to anthropogenic climate change. Nevertheless, these extreme events may be modulated by large-scale climate variability modes across a wide range of spatial and temporal scales. Using large ensemble multi-model