Healthcare Multimodal AI Foundation Scientist

Aimlroles; Precinct (MA); Sur place; USD 129 000 - 177 000; Plein temps

Avantages offerts par ce poste

Medical insurance

Dental insurance

Vision insurance

401(k) retirement plan

Life insurance

Disability insurance

Paid parking/public transportation

Paid time off

Paid sick time

Résumé du poste

Siemens Healthineers is seeking a Foundation AI Research Scientist to advance multimodal foundation models for healthcare, including medical imaging and clinical data. You will design, train, and evaluate models that learn across images, text, and patient history, collaborating with AI scientists, engineers, and clinicians.

You will explore novel architectures, distillation, and few-/zero-shot learning to scale AI capabilities across medical findings.

Qualifications

• PhD in Computer Science, Electrical Engineering, Biomedical Engineering, or related field.
• Demonstrated research in ML/DL.
• Strong understanding of modern DL architectures and training methods.
• Experience with foundation models and multimodal learning.
• Familiarity with medical imaging AI.
• Excellent programming skills in deep learning frameworks.

Responsabilités

• Designing and developing large-scale multimodal foundation models for healthcare.
• Researching next-generation AI architectures and learning strategies.
• Developing model distillation, transfer learning, and few-shot/zero-shot methods.
• Advancing multimodal AI across medical images, text, and health data.
• Collaborating with researchers, engineers, and clinicians to deploy systems.

Connaissances

Foundation models

Multimodal learning

Vision-language models

Medical imaging AI

Deep learning

Model distillation

Few-shot learning

Zero-shot learning

Scientific communication

Formation

PhD in CS/EE/BME

Strong ML/DL background

Outils

PyTorch

TensorFlow

Description du poste

Siemens Healthineers is seeking a Foundation AI Research Scientist to advance multimodal foundation models for healthcare, including medical imaging and clinical data. You will design, train, and evaluate models that learn across images, text, and patient history, collaborating with AI scientists, engineers, and clinicians.

You will explore novel architectures, distillation, and few-/zero-shot learning to scale AI capabilities across medical findings.