Postdoc: Pioneering Multimodal Cardiovascular AI Research

AcademicTransfer; Netherlands; On-site; EUR 42,000 - 65,000; Full time

Benefits offered by this job

Bike scheme

Public transport reimbursement

BeFrank pension

End-of-year bonus (8.3%)

Job summary

Amsterdam UMC Research BV invites applications for a postdoctoral project focused on developing innovative multimodal AI frameworks to integrate diverse cardiovascular data sources. The role emphasizes designing architectures for cross-modal representations, synthetic data generation, and validation with clinical datasets in collaboration with cardiologists.

You will mentor PhD and MSc students and present findings at international conferences, with the potential to apply for grants to grow the

Qualifications

• PhD in Computer Science, AI/ML, Biomedical Engineering, or related field.
• Strong programming skills in Python and experience with deep learning frameworks (e.g., PyTorch).
• Experience in medical image analysis and multimodal learning is a plus.
• Publication record in top AI/ML or medical informatics venues is preferred.
• 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.
• Pursue grants to expand the research group.

Skills

Python programming

PyTorch

High Performance Computing

Medical image analysis

Multimodal learning

Publication track record

Clinical data experience

Education

PhD in Computer Science / AI/ML / Biomedical Engineering

Tools

PyTorch

HPC

Job description

Amsterdam UMC Research BV invites applications for a postdoctoral project focused on developing innovative multimodal AI frameworks to integrate diverse cardiovascular data sources. The role emphasizes designing architectures for cross-modal representations, synthetic data generation, and validation with clinical datasets in collaboration with cardiologists.

You will mentor PhD and MSc students and present findings at international conferences, with the potential to apply for grants to grow the