3D Medical Image DL Architect — Multimodal Segmentation

Italian Ministry of Education, University and Research; Italia; Vor Ort; EUR 32.000 - 45.000; Vollzeit

Zusammenfassung

Unimore in Italy seeks a researcher to advance deep learning methods for segmentation and analysis of 3D medical volumes, including Cone-Beam CT and brain MRI. The appointment targets candidates with strong neural-network skills and medical imaging experience.

The role involves designing, training and evaluating architectures (CNNs, Transformers, State Space Models) with emphasis on scalability on HPC/GPU environments and collaboration with imaging teams.

Qualifikationen

• Experience in deep learning for 3D medical image analysis.
• Familiarity with CBCT and MRI modalities.
• Proven ability to design and evaluate neural architectures.

Aufgaben

• Develop deep learning methods for segmentation of 3D medical volumes.
• Evaluate architectures (CNNs, Transformers, State Space Models) for accuracy and efficiency.
• Implement multimodal fusion and image synthesis techniques.

Kenntnisse

Deep learning

3D medical image segmentation

Convolutional neural networks

Transformer architectures

State Space Models

High-performance computing

Tools

Mamba

GPU HPC

Jobbeschreibung

Unimore in Italy seeks a researcher to advance deep learning methods for segmentation and analysis of 3D medical volumes, including Cone-Beam CT and brain MRI. The appointment targets candidates with strong neural-network skills and medical imaging experience.

The role involves designing, training and evaluating architectures (CNNs, Transformers, State Space Models) with emphasis on scalability on HPC/GPU environments and collaboration with imaging teams.