ppOrganisation/Company Università di Pavia Research Field Biological sciences Researcher Profile Recognised Researcher (R2) Leading Researcher (R4) First Stage Researcher (R1) Established Researcher (R3) Application Deadline 2 Sep 2026 - 12:00 (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 /p h3Offer Description /h3 pIn collaboration with a team of engineers from the Università della Svizzera italiana, an Artificial Intelligence (AI) tool based on 3D deep learning techniques, including convolutional neural networks and Single Shot Detector (SSD) algorithms, will be developed to automatically detect and localize ovarian follicles from nano-computed tomography (nanoCT) image datasets. The primary objective of this tool is to automate follicle classification, improving both accuracy and scalability compared with manual annotation and classification. /p pThe public call with detailed attendance and selection rules (Art 4 and 6) can be found at: selections are open to candidates, Italian or foreigner, in possession, on the date of the deadline for submitting applications for the admission to the selection, of a master's degree or single-cycle, degree obtained no more than six years previously are eligible to participate in the selection process.



These degrees must be relevant to the subject of the research activity. /p pFurther specific assessable qualifications (see Art. 1 par. 1 Call for applications): /p pThe following will be considered preferential qualifications: /p ulliMaster's degree in Applied Experimental Biology, specializing in Molecular Biomedical Sciences (Class LM-6); /liliPhD in Bioengineering, Bioinformatics, and Health Technologies /li /ul pA strong background in mammalian gametogenesis and reproductive biology will be required, together with demonstrated experience in the preparation of soft tissue samples for computed tomography (CT) analysis and in the evaluation of tomographic image datasets. Knowledge of Artificial Intelligence (AI) models, particularly in the field of Computer Vision (e.g., Convolutional Neural Networks and Vision Transformers), will be considered an asset, as these approaches will be employed in collaboration with engineering colleagues. /p ulliAFRICA /liliEUROPE /liliOCEANIA /liliNORTH AMERICA /liliSOUTH AMERICA /liliASIA /liliOTHER /li /ul pbEligibility of fellows: country/ies of residence: /b /p ulliAFRICA /liliEUROPE /liliOCEANIA /liliNORTH AMERICA /liliSOUTH AMERICA /liliASIA /liliOTHER /li /ul pbEligibility of fellows: nationality/ies: /b /p ulliAFRICA /liliEUROPE /liliOCEANIA /liliNORTH AMERICA /liliSOUTH AMERICA /liliASIA /liliOTHER /li /ul h3Selection process /h3 /p #J-18808-Ljbffr

📌 A Digital Atlas of the Mammalian Ovary:Development of an Artificial Intelligence (AI) Tool for the Automatic Detection of Ovarian Follicles in Images Obtained by Nano-Computed Tomography (nanoCT) of the Murine Ovary
🏢 Italian Ministry of Education, University and Research
📍 Roma