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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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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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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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, Bulk RNAseq), molecular modeling, and structural bioinformatics. Mandatory Requirements: • PhD in Genetics, Genomics, Bioinformatics, or related fields (completed within the last 7 years); • Proven and
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of the main project; 2. Improve proficiency in the inverse modeling techniques provided by the PEST software, and apply them to the experimental data for calibration of the MFLUX model, as specified in the main
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of the doctorate diploma, curriculum summary according to the model established by FAPESP (São Paulo Research Foundation, grantor institution). * Letter explaining motivation, description of the product in mind
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state, Brazil) is offering one post-doctoral position funded by FAPESP, the São Paulo Research Foundation. The project involves developing combinatorial optimization models and methods applied to packing
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water quality parameters and predict cyanobacteria blooms in the Tietê system reservoirs. Activities: 1. Develop machine learning models for estimating water quality parameters via remote sensing; 2