Deep learning and synthetic data generation methods for automated analysis of volumetric images of human and mouse brains acquired by light-sheet fluorescence microscopy

pOrganisation/Company LENS Research Field Physics » Biophysics Researcher Profile Recognised Researcher (R2) Leading Researcher (R4) First Stage Researcher (R1) Established Researcher (R3) Application Deadline 6 Oct 2026 - 23:59 (UTC) Country Italy Type of Contract To be defined Job Status Not Applicable Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No /ph3Offer Description /h3pThe research activity will focus on the processing and analysis of large volumetric images acquired bybr/light-sheet fluorescence microscopy from human and mouse brains, within the Human Optical Brainbr/Mapping project. The work will involve the development and implementation of advanced computationalbr/methods for automated image analysis, with particular attention to segmentation, quantitativebr/information extraction, and comparison across datasets acquired under different experimentalbr/conditions. /ppMaster degree in Biomedical Engeneeringbr/Expertise in analysis of volumetric fluorescence images, programming, deep learning, and machine learning.br/Experience with Python and major libraries for image processing and neural networks; knowledge ofbr/segmentation methods, domain adaptation and/or generative models for synthetic data. Experience with lightsheetbr/fluorescence microscopy images, large 3D datasets, annotated ground truth management, and highperformancebr/computing environments will be considered an advantage /pulliItaly /li /ulpbEligibility of fellows: country/ies of residence: /b /pulliEUROPE /li /ul #J-18808-Ljbffr