Deep learning and synthetic data generation methods for automated analysis of volumetric images of h
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Organisation/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
Offer Description The research activity will focus on the processing and analysis of large volumetric images acquired by
light-sheet fluorescence microscopy from human and mouse brains, within the Human Optical Brain
Mapping project. The work will involve the development and implementation of advanced computational
methods for automated image analysis, with particular attention to segmentation, quantitative
information extraction, and comparison across datasets acquired under different experimental
conditions.
Master degree in Biomedical Engeneering
Expertise in analysis of volumetric fluorescence images, programming, deep learning, and machine learning.
Experience with Python and major libraries for image processing and neural networks; knowledge of
segmentation methods, domain adaptation and/or generative models for synthetic data. Experience with lightsheet
fluorescence microscopy images, large 3D datasets, annotated ground truth management, and highperformance
computing environments will be considered an advantage
Italy
Eligibility of fellows: country/ies of residence:
EUROPE
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