Machine Learning R&D Engineer - X-ray nanoimaging

The ESRF-EBS upgrade fostered the rapid development of X-ray nanoimaging for life sciences. In particular, X-ray holographic nanotomography is becoming a key technology for large-scale neuronal imaging, and bioimaging more broadly. This raises new challenges in image processing and analysis. Automated approaches for extracting information and biomedical knowledge from the multi-TB X-ray nanotomography data are necessary. At the same time, Machine Learning (ML) approaches can contribute to the improvement of image reconstruction accuracy and data acquisition acceleration, enabling to fully benefit from the EBS source. Instrumentation developments planned at the ESRF will further expand X-ray nanoimaging capabilities, particularly for brain connectomics. In this context, you will play a key role in ML developments for image processing and analysis tailored to large-scale X-ray nanoimaging.

You will develop and deploy cutting-edge ML based methods for image processing and analysis in X-ray nanoimaging. Your developments will aim to improve precision and speed in coherent X-ray microscopy and you will build automated methods for image analysis, including image segmentation for connectomics. You will develop robust and efficient code, suitable for processing large-scale 3D image data, and usable by other researchers and engineers. Preferably, you will disseminate your work in high quality scientific papers.