CONTEXT & JOB DESCRIPTION
Tomography is one of the most important synchrotron techniques, with applications ranging from soft condensed matter to metallurgy. It provides access to three dimensional information of different types of contrast (e.g. absorption, phase, fluorescence or diffraction-contrast, holo- or ptycho-tomography). The much increased photon flux of the ESRF-EBS, combined with new generation 2D detectors (faster, larger), presents both new scientific opportunities and important challenges regarding data processing and analysis.
You will join the team of scientists and software engineers working on the development of a dedicated tomography analysis software suite (nabu, tomwer). You will contribute high-performance code to enable fast processing for various applications, possibly including: tomography pipelines, diffraction or fluorescence computed tomography reconstructions, etc.
You will also conduct an original research programme applying and expanding tomography capabilities in collaboration with ESRF beamlines, e.g. using machine learning for the analysis of low-intensity datasets or tailored segmentation, new iterative reconstruction algorithms…
The work will take place in the Algorithms & scientific Data Analysis group, in close collaboration with imaging beamlines. Further information about the post can be obtained from Nicola Vigano (email@example.com), Pierre Paleo (firstname.lastname@example.org) and Vincent Favre-Nicolin (email@example.com).
Your missions include:
- The development, implementation, and optimisation of tomography algorithms within the tomography software suite (https://www.silx.org/pub/nabu/doc/).
- Conducting an original research project, exploiting and expanding tomography techniques.
- PhD degree or equivalent in Physics, Computer Science, Engineering, Science or similar area
- Strong programming skills in Python are essential, notably for the implementation of optimisation and reconstruction algorithms
- Synchrotron-based X-ray computed tomography experience is a strong asset
- Experience in Machine Learning or GPU programming (CUDA, OpenCL) is a plus
- A strong background in natural sciences or mathematics is an advantage
- Curiosity and good communication skills, and being a team player is required, in order to work with engineers and scientists on different techniques and beamlines
- Proficiency in English (working language at the ESRF
What we offer:
- Be inspired by our innovative research institute, with an international workforce from 38 different countries
- Collaborate with global experts on real-world science
- Come and live in a vibrant city, in the heart of the Alps, and Europe’s Green Capital 2022
- Enjoy a workplace designed to support your quality of life
- Benefit from our competitive compensation and allowances package, including financial support for your relocation to Grenoble
For further information on employment terms and conditions, please refer to https://www.esrf.fr/home/Jobs/what-we-offer.html
The ESRF is an equal opportunity employer and encourages applications from disabled persons.
To apply for this job please visit esrf.gestmax.eu.