Book a call
Book a call

PhD Position: AI for Medical Image Analysis in Neuromuscular Diseases — IBiS / University of Seville

PhD Position

POSITIONS

A fully funded, 3-year PhD position is open at the Instituto de Biomedicina de Sevilla (IBiS) — a joint centre of Hospital Universitario Virgen del Rocío, CSIC, and the University of Seville — for a newly funded project on AI-driven medical image analysis and clinical decision support in neuromuscular diseases.

The project: develop deep learning approaches that extract clinically relevant information from routine diagnostic images, helping clinicians improve detection and characterization of neuromuscular disease.

Research areas: neuromuscular diseases, deep learning & computer vision, bioimage analysis, CNNs, vision transformers, explainable AI, and foundation models in bioimaging.

Required:

  • European ID

  • MSc in Computer Science, AI, Data Science, Bioinformatics, Biomedical Engineering, Mathematics, or Physics

  • Strong programming skills

  • Excellent written and spoken English

  • Genuine motivation to pursue a PhD (candidate will be enrolled in the "Biología Integrada" programme at the University of Seville)

Desirable:

  • Spanish speaker

  • Experience in computer vision / image analysis

  • PyTorch or TensorFlow experience

  • Knowledge of CNNs and/or Vision Transformers

  • Experience with biomedical or medical imaging data

  • Familiarity with Git and scientific computing environments

To apply: send a CV with academic records and a short statement of research interests.

📍 Seville, Spain · 🕒 Full-time, 3 years, fully funded · 📅 Start expected in 2026 (CSyC 2026 – FEDER digital health & AI projects)

Click to Apply

A fully funded, 3-year PhD position is open at the Instituto de Biomedicina de Sevilla (IBiS) — a joint centre of Hospital Universitario Virgen del Rocío, CSIC, and the University of Seville — for a newly funded project on AI-driven medical image analysis and clinical decision support in neuromuscular diseases.

The project: develop deep learning approaches that extract clinically relevant information from routine diagnostic images, helping clinicians improve detection and characterization of neuromuscular disease.

Research areas: neuromuscular diseases, deep learning & computer vision, bioimage analysis, CNNs, vision transformers, explainable AI, and foundation models in bioimaging.