About the Role
We are seeking a passionate and skilled Research Assistant. You will work at the intersection of healthcare and artificial intelligence, developing transformer-based models and large language models (LLMs) to support applications in clinical decision-making, medical imaging, and drug discovery.
This role offers the opportunity to work with rich, real-world healthcare data, including electronic health records (EHR) and medical images, to build AI tools with direct translational impact in the local healthcare system.
Responsibilities
- Research, design, and train transformer-based and deep learning models for healthcare and biomedical applications
- Develop AI systems that integrate multimodal data, such as EHRs and medical imaging
- Contribute to drug discovery projects through generative models, knowledge graphs, and other AI techniques
- Deploy models in hybrid cloud environments for research or operational use
- Collaborate with software engineers to build functional AI applications and prototypes
- Document methodologies clearly, including model development, validation, and deployment pipelines
- Support the preparation of research publications, presentations, and grant proposals
Requirements
- Master's degree in bioinformatics, computer science, biomedical informatics, statistics, or a related field
- Hands-on experience in deep learning, especially in domains like NLP, imaging, or drug discovery
- Strong proficiency in Python and experience with PyTorch, TensorFlow, Hugging Face Transformers, and scikit-learn
- Experience with LLM fine-tuning, transformer architectures, or multimodal learning is a strong advantage
- Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and deployment of ML pipelines
- Experience working with healthcare data, including structured EHRs or medical imaging, is highly desirable
- Excellent problem-solving, communication, and documentation skills
- Ability to work independently and collaboratively in a multidisciplinary team
