Multimodal AI Researcher for Cardiac Death Prediction

Komwerkeninzorgenwelzijn; Amsterdam; On-site; EUR 42,000 - 66,000; Full time

Job summary

Amsterdam UMC Research BV is seeking an ambitious postdoctoral researcher with expertise in AI/ML to develop multimodal frameworks for cardiovascular data, integrating imaging, signals, and genomics. You will work in Dr.

Fleur Tjong’s group within the TjongLab at Amsterdam UMC, collaborating with cardiologists and international AI researchers to advance predictive models. You will design novel architectures, generate synthetic data, and optimize cross-modal representations, with opportunities to

Qualifications

• PhD in Computer Science, AI/ML, Biomedical Engineering, or related field.
• Strong programming skills in Python and experience with PyTorch; HPC experience is a plus.
• Experience in medical image analysis; multimodal learning is a plus.
• Publication track record in top AI/ML or medical informatics venues.
• 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.
• Intention to apply for grants to expand our group, and potentially start your own research group.

Skills

Python

PyTorch

Medical imaging

Multimodal learning

HPC

Education

PhD in CS/AI

Biomedical Eng

Tools

PyTorch

HPC

Job description

Amsterdam UMC Research BV is seeking an ambitious postdoctoral researcher with expertise in AI/ML to develop multimodal frameworks for cardiovascular data, integrating imaging, signals, and genomics. You will work in Dr.

Fleur Tjong’s group within the TjongLab at Amsterdam UMC, collaborating with cardiologists and international AI researchers to advance predictive models. You will design novel architectures, generate synthetic data, and optimize cross-modal representations, with opportunities to