Pica Code-099 Segmentation and multimodal analysis of 3D medical images through efficient deep learning architectures
pOrganisation/Company Unimore Research Field Engineering » Computer engineering Researcher Profile Recognised Researcher (R2) Leading Researcher (R4) First Stage Researcher (R1) Established Researcher (R3) Application Deadline 18 Nov 2026
- 13:00 (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 /ph3Offer Description /h3pResearch activities: The appointment concerns the development of deep learning methods for the segmentation and analysis of three-dimensional medical volumes, with particular reference to Cone-Beam CT (CBCT) images of the maxillofacial region and brain magnetic resonance imaging (MRI). Activities will include: /pullidesign,
training and evaluation of architectures for multi-structure 3D segmentation, including convolutional, Transformer and State Space Model (e.g., Mamba) architectures, with attention to computational efficiency and scalability on HPC/GPU infrastructures; /lilidevelopment of multimodal fusion strategies and methods to handle missing modalities (e.g., incomplete MRI sequences), as well as image synthesis methods;(omissis) /li /ululliItaly /li /ulpbEligibility of fellows: country/ies of residence: /b /pulliOTHER /li /ulpbEligibility of fellows: nationality/ies: /b /pulliOTHER /li /ulh3Selection process /h3pselective public procedure based on qualifications /p #J-18808-Ljbffr
- 13:00 (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 /ph3Offer Description /h3pResearch activities: The appointment concerns the development of deep learning methods for the segmentation and analysis of three-dimensional medical volumes, with particular reference to Cone-Beam CT (CBCT) images of the maxillofacial region and brain magnetic resonance imaging (MRI). Activities will include: /pullidesign,
training and evaluation of architectures for multi-structure 3D segmentation, including convolutional, Transformer and State Space Model (e.g., Mamba) architectures, with attention to computational efficiency and scalability on HPC/GPU infrastructures; /lilidevelopment of multimodal fusion strategies and methods to handle missing modalities (e.g., incomplete MRI sequences), as well as image synthesis methods;(omissis) /li /ululliItaly /li /ulpbEligibility of fellows: country/ies of residence: /b /pulliOTHER /li /ulpbEligibility of fellows: nationality/ies: /b /pulliOTHER /li /ulh3Selection process /h3pselective public procedure based on qualifications /p #J-18808-Ljbffr