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Brazilian Synchrotron Light Laboratory

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Postdoctoral Opportunity in X-ray Tomography and Scientific Computing Brazilian Synchrotron Light Laboratory in Brazil

Degree Level

Postdoc

Field of study

Computer Science

Funding

FAPESP-funded postdoctoral fellowship at R$ 12,570 per month plus a research allowance.

Deadline

Oct 30, 2026

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Country

Brazil

University

Brazilian Synchrotron Light Laboratory

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Keywords

Computer Science
Electrical Engineering
Materials Science
Computational Science
Python Programming
X-ray Imaging
Image Reconstruction
High Performance Computing
Gpu Computing
Computational Imaging
Inverse Problem
Programming Language
Physics

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About this position

Postdoctoral opportunity in X-ray tomography and scientific computing at the MOGNO beamline (Sirius/LNLS-CNPEM) in Campinas, Brazil.

This is a FAPESP-funded postdoctoral fellowship within a collaborative project between LNLS/CNPEM and Ghent University (Belgium), focused on developing and optimizing computational methods for high-speed, time-resolved X-ray tomography.

Ideal candidates should have experience in scientific programming, image reconstruction, Python, high-performance computing, and preferably C/C++, CUDA, GPU computing, computational imaging, inverse problems, tomographic reconstruction, unconventional acquisition geometries, and large-scale data processing.

The fellowship offers R$ 12,570/month plus a research allowance. The position is located in Campinas, Brazil, with an expected start in January 2027.

Application deadline: October 30, 2026. Interested applicants should follow the full details and application instructions in the linked opportunity page.

Funding details

FAPESP-funded postdoctoral fellowship at R$ 12,570 per month plus a research allowance.

What's required

Experience in scientific programming and image reconstruction is required. Strong Python skills and high-performance computing experience, including C/C++, CUDA, and GPU computing, are desired. Background in computational imaging, inverse problems, tomographic reconstruction, unconventional acquisition geometries, and large-scale data processing is particularly welcome.

How to apply

Read the full details and application instructions at the provided link. Submit the application according to the instructions in the linked opportunity page before the deadline.

More information can be found here

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