Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
-
Field
-
learning methods will be applied to link small-scale experimental data and numerical simulations to large-scale reservoir models. This approach aims to more accurately capture the complex heterogeneity
-
and electronic states; • Inductively coupled plasma techniques (ICP-OES/MS) for compositional and elemental analysis. - Familiarity with advanced characterization methods at large-scale facilities
-
(ICP-OES), mass spectrometry or graphite furnace atomic absorption spectrometry (GF-AAS); 3) Experience in data analysis and statistical tools: cluster analysis and principal component analysis; 4
-
incorporating local constraints (stress, displacement, temperature) via the Augmented Lagrangian method and global compliance constraints, applying coupled thermomechanical simulations to predict performance in
-
theoretical concepts such as the multifunctionality of agriculture, agroecology, food sovereignty, and short marketing circuits, offering elements for the internationalization of research and reflection
-
of biomarkers (glucose, uric acid, and lactic acid), using flexible polymeric substrates and surface modification with metal oxides synthesized via CO2 laser. Sensors will be coupled with a miniaturized NFC
-
planets, and trans-Neptunian objects in retrograde motion. Traditional orbital dynamics methods will be combined with machine learning techniques, such as convolutional neural networks and Vision
-
, qualitative methods, and AI-based tools is desirable. Fellowship Details Funding agency: São Paulo Research Foundation (FAPESP) Modality: Postdoctoral Fellowship Monthly value: R$ 12,570.00 Duration: 24 months