Computational scientist in coherent X-ray imaging

The Extremely Brilliant Source upgrade of the ESRF has led to two orders of magnitude increase in the available coherent X-ray flux. This primarily benefits techniques like coherent diffraction imaging (CDI), holo-tomography, ptychography which can image samples in three dimensions with an increased speed and resolution. One important challenge remains in iterative reconstruction algorithms, which require a lot of processing. This is currently developed at ESRF with the open-source PyNX software suite which exploits graphical processing units (GPU) for accelerated reconstructions enabling online data analysis.

You will drive software development to exploit coherent beams at ESRF, notably in the field of far-field (including Bragg geometry) or near-field imaging. The position will present particular challenges in the development of phasing algorithms, data processing, visualization. You will explore new avenues in coherent imaging, e.g. exploiting machine learning or introducing new techniques exploiting the EBS-enhanced coherent photon flux. You will also contribute to the maintenance of analysis pipelines for ESRF beamlines.

The work will take place in the Algorithms & scientific Data Analysis group, in close collaboration with coherent imaging beamlines. Further information about the post can be obtained from Vincent Favre-Nicolin (favre@esrf.fr).

Your missions include: 

• The development, implementation, and optimisation of novel algorithms and data processing modules, notably with the PyNX software (http://ftp.esrf.fr/pub/scisoft/PyNX/)
• Support ESRF beamlines exploiting coherent X-ray imaging techniques
• Conduct an original research project exploiting coherent X-ray imaging in collaboration with ESRF beamlines scientists, e.g. with original techniques or algorithms allowing to better exploit the EBS-enhanced coherent photon flux