Postdoc: Innovate Multimodal AI for Cardiology

Amsterdam UMC; Amsterdam; On-site; EUR 42,000 - 65,000; Full time

Benefits offered by this job

12-month contract

Salary scale 10 (€3,724–€5,867) gross

8.3% end-of-year bonus

Public transport reimbursement

Bike scheme

BeFrank pension

Job summary

Amsterdam UMC Research BV invites applications for a postdoctoral researcher to design and implement multimodal AI architectures for cardiovascular applications. You will develop synthetic data to augment sparse modalities and create joint optimization frameworks for cross-modal representations.

You will validate models with clinical datasets in collaboration with cardiologists and mentor PhD/MSc students, presenting findings at international conferences and potentially starting your own

Qualifications

• PhD in a relevant field (CS/AI/biomedical engineering).
• Strong programming in Python; experience with PyTorch; HPC experience a plus.
• Experience in medical image analysis; multimodal learning is a plus.
• Publication record in top AI/ML or medical informatics venues (NeurIPS, MICCAI, SPIE, Nature portfolio).
• Experience with clinical healthcare data systems is a plus.

Responsibilities

• Design and implement novel multimodal AI architectures for cardiovascular applications.
• Develop synthetic data generation methods to augment sparse modalities.
• Create frameworks for joint optimization of cross-modal representations.
• Validate models using clinical datasets in collaboration with cardiologists.
• Mentor PhD and MSc students and present findings at international conferences.

Skills

Python

PyTorch

Medical imaging

Multimodal learning

Publication track record

Education

PhD in CS/AI/Biomedical Eng

Job description

Amsterdam UMC Research BV invites applications for a postdoctoral researcher to design and implement multimodal AI architectures for cardiovascular applications. You will develop synthetic data to augment sparse modalities and create joint optimization frameworks for cross-modal representations.

You will validate models with clinical datasets in collaboration with cardiologists and mentor PhD/MSc students, presenting findings at international conferences and potentially starting your own