Research theme area:
Fluid Mechanics, advanced image analysis, noise removal, pressure field reconstruction, and particle image velocimetry.
Abstract:
The candidate will collaborate with researchers from the FAPESP-Shell Research Centre for Greenhouse Gas Innovation of POLI-USP at the University of São Paulo. Summary of the program and projects can be found at the RCGI website (https://sites.usp.br/rcgi/).
The selected candidate will employ machine learning and other techniques based on the NavierStokes equations to perform flow analysis with a focus on noise removal and pressure field reconstruction. The candidate is expected to work with experimental and numerical data, especially from electrolyzer and fuel cell flows.
Description:
The applicant will contribute in line with the main objectives of the project:
- Work with flows obtained by computational fluid dynamics simulation, synthetic images or experimentally.
- Use and/or develop computational algorithms (filters and/or neural networks) to remove noise from flow images.
- Develop computational algorithms capable of reconstructing pressure fields using velocities obtained either through computational fluid dynamics data, synthetic images or particle image velocimetry images.
- Test the developed algorithms in electrochemical reactor flows, such as electrolyzers and fuel cells.
- Understand experimental and numerical methods related to fluid mechanics.
- Collaborate closely with a multidisciplinary team of researchers to integrate their studies in different areas.
- Be able to perform experiments with optical techniques such as particle image velocimetry.
Requirements to fill the position:
We are seeking a highly motivated candidate with a PhD in Engineering or a related field, with solid experience in advanced image analysis applied to fluid mechanics. A strong publication record, experience in multidisciplinary research environments, experience in intellectual property production (patents, software registrations, and journal articles) are highly desirable. Proficiency in English is required.
INFORMATION ABOUT FELLOWSHIP:
This Postdoc fellowship is funded by FAPESP. The fellowship will cover a standard maintenance stipend per month whose amount is available at https://fapesp.br/valores/bolsasnopais.
MORE INFORMATION:
https://sites.usp.br/rcgi/opportunities/
Position: Post-Doctoral Fellowship REF.: 25PDR319
Access here AND APPLICATION AT REF Post-Doctoral REF.: 25PDR319
