• Support research activities in deep learning, artificial intelligence, machine learning, and data analytics across multidisciplinary projects involving biomedical, clinical, imaging, and other complex datasets. Assist with data preprocessing, model development, implementation, training, validation, and performance evaluation using modern AI and statistical techniques. Contribute to software development, data visualization, technical documentation, literature reviews, and preparation of research publications in high impact journals, presentations, and grant proposals. Collaborate effectively with faculty, research staff, and students while supporting ongoing research initiatives in a flexible, team-oriented environment.

The ideal candidate has MS or PhD degree with a background in computer science, data science, engineering, statistics, mathematics, or a related quantitative discipline, with experience in deep learning, machine learning, programming, and data analytics. Recent graduates, or professionals with relevant research or industry experience are encouraged to apply. The candidate should possess strong analytical and problem-solving skills, be able to work independently and collaboratively, and demonstrate effective communication and technical documentation abilities. Experience with Python, PyTorch, TensorFlow, data visualization, cloud computing, or biomedical data analytics is desirable. This position is designed to accommodate applicants with a broad range of AI, data science, and computational research expertise while providing opportunities to contribute to cutting-edge multidisciplinary research projects.