Microscope Image Analyst

The candidate will be in charge of servicing the Electron Microscopy (EM) Platform of ISABIAL. The Electron Microscopy Platform of ISABIAL wants to implement Artificial Intelligence (AI) to analyze the large volumes of data generated by high-resolution 2D and 3D imaging. The objective is to apply machine learning and image processing techniques (Machine and Deep Learning, based on convolutional neural networks) to improve the quality and speed of image analysis, as well as to extract relevant information from the datasets generated with fluorescence/confocal and electron microscope sampling to do CLEM (Correlative Light Electron Microscopy). To achieve this, the candidate will be in charge of establishing a workflow that will allow the automated processing and analysis of the datasets in an efficient and reliable manner. This workflow will be designed to be reproducible and standardized so that it can be used by other researchers and laboratories working with electron microscopy, Volume EM, CLEM and fluorescence/confocal image analysis. The main functions and tasks to be performed will be, among others: – Technical advice to users on the most suitable software and tools for the Interpretation, analysis and quantification of datasets (Fiji, Image J, Icy, MATLAB, CebraEM, CLEMsite, Mobius, QuPath, Arivis 4D, IMARIS, Webknossos, R, Python, Cell Profiler, …). – Management and storage of microscope files (images, datasets, backups). – Establish workflows: Image interpretation, segmentation, analysis and quantification by AI (Machine and Deep Learning: Ilastick, MIB, Apeer, …). – Connection and analysis in connection to computational cluster and servers. – Train future users of the image analysis service. – Training and coaching future personnel of other services with which the platform collaborates. – Quality control and maintenance of computer equipment and workstations. – Help search for new funding sources for the platform and training courses.