About the role
AI summarisedSenior scientist role focused on advancing AI/ML research for healthcare applications, developing novel architectures and training methods for large language models and multimodal AI systems, with emphasis on clinical translation and commercialization.
ResearchOnsite
Key Responsibilities
- Develop novel architectures, training strategies, and optimization methods for LLMs, agentic AI, vision foundation model and multimodal foundation models
- Design and implement multimodal learning pipelines that integrate text, imaging, omics, and real-world clinical data
- Prototype AI systems for clinical and biomedical applications (e.g., decision support, conversational AI, population health, drug discovery)
- Benchmark models against state-of-the-art healthcare AI datasets and evaluation frameworks
- Collaborate with industry and healthcare partners to enable translation, licensing, and commercialization
- Publish in top-tier AI/ML venues (e.g., NeurIPS, ICML, ICLR, AAAI, ACL) and high-impact biomedical journals (e.g., Nature Medicine)
- Contribute to open science initiatives (datasets, model releases, benchmarks)
- Secure funding through collaborative research proposals with academia, healthcare institutions, and industry
Requirements
- PhD in Computer Science, Artificial Intelligence, Machine Learning, or related fields
- Strong publication record in top AI/ML venues (e.g., NeurIPS, ICML, ICLR, ACL) or high-impact biomedical journals
- Deep expertise in LLMs, vision foundation models, or multimodal AI
- Strong skills in deep learning frameworks (PyTorch, TensorFlow, JAX) and distributed/HPC training
- Experience in large-scale LLM and/or foundation model training and deployment
- Experience with medical or biomedical data (EHR, clinical notes, imaging, genomics)
- Familiarity with biomedical ontologies and knowledge graphs (UMLS, SNOMED CT, PubMed)
- Understanding of AI ethics, safety, and regulatory considerations in healthcare