Scientist for machine learning synchrotron applications

Context & Job description

The Extremely Brilliant Source upgrade of the ESRF has led to a significant increase in the acquisition speed and the amount of data which must be processed and analysed by the end users. It is therefore essential to provide advanced tools to enhance the acquisition and data analysis strategies, and provide online (live during experiments) feedback to the ESRF users.

We are looking to recruit two 5-year scientists to work on machine learning developments in two main areas : firstly, for tomography , e.g. for applications like denoising, super-resolution, segmentation or improved data collection. And secondly for scattering / diffraction applications, notably (but not exclusively) for structural biology , where the standardisation of techniques makes it a prime target for smarter automation to improve the data quality and the acquisition efficiency.

Your missions include :

The development and deployment of innovative machine-learning based algorithms for data acquisition and online data processing, in the fields of scattering / diffraction (notably structural biology) and tomography

Conduct an original research project exploiting machine learning for synchrotron applications with ESRF beamlines scientists

Work with scientists and engineers at ESRF and with partner institutions to expand and disseminate knowledge about the use of ML for synchrotron applications

Expected profile

PhD degree in Physics, Biology, Computer Science, Science or similar area

At least 4 years of experience in machine (deep) learning developments (can include PhD years), ideally for synchrotron data analysis or similar

Strong programming skills in Python in the field of experimental data analysis are required, including usual deep learning toolkits. GPU programming (CUDA, OpenCL) is a plus.

Curiosity, good communication skills and being a team player is required, in order to work with engineers and scientists with different techniques and beamlines.

• Proficiency in English (working language at the ESRF

Working conditions

The salary will be calculated on the basis of relevant qualifications and professional experience.

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What we offer :