Post-Doctoral Associate in the Division of Engineering - Dr Farah Shamout

Nyu-Abu Dhabi • San Francisco, CA

85d

About The Position

The Clinical Artificial Intelligence Lab at NYU Abu Dhabi seeks to improve patient care by developing new machine learning methodologies that tackle unique computational problems in healthcare applications. We use large real-world complex datasets, including data extracted from electronic health records and medical images, for applications pertaining to patient diagnostics and prognostics. We are seeking a Postdoctoral Researcher to join the team and make significant contributions to the field. The researcher is expected to have (i) strong machine learning skills to improve model performance and robustness, and (ii) exemplary passion and motivation to pursue multidisciplinary research at the intersection of computing and healthcare. Methodologies of interest include: Multi-modal learning, Foundation models, including large language models, Agentic AI, Multi-agent AI systems, Transfer learning, Self-supervised learning, Federated learning. The Postdoctoral Researcher will be primarily based at NYU Abu Dhabi. The researcher will report directly to Dr. Farah Shamout and work in close collaboration with other researchers, PhD students, and undergraduate research assistants. The researcher will engage with our regular collaborators across the NYU campuses and local medical institutions in the UAE.

Requirements

• Currently has or is in the process of completing a PhD, MD/PhD, DPhil or equivalent terminal degree from a recognized institution (no more than 5 years since completing the doctoral degree)
• Doctoral research in the area of machine learning and artificial intelligence
• Bachelor's/ Master's degree in computer science, mathematics, computer engineering, or relevant technical field
• First-author peer-reviewed published papers (or under review)
• Proficient programming experience in Python and libraries (e.g., Pytorch, TensorFlow) with several years of practice
• Experience in maintaining high-quality code on Github
• Experience in running and managing experiments using GPUs
• Ability to visualize experimental results and learning curves
• Effective inter-personal and team-building skills
• Self-motivated with an ability to work independently and in a team to get the work done
• Excellent communication skills (oral and written communication)
• Willingness to learn and confront new challenges

Nice To Haves

• Doctoral research conducted in the area of machine learning for healthcare and related topics
• Deep knowledge of multi-modal learning, transfer learning, foundation models, and self-supervised learning
• Experience in dealing with large medical datasets (e.g., electronic health records data or medical images)
• Ability to use high performance computing cluster

Responsibilities

• Support the supervisor in developing and implementing the research agenda
• Conduct high-quality and innovative research primarily focused on ML methodology development for healthcare
• Generate new high-impact ideas based on gaps and limitations of the state-of-the-art (SOTA)
• Design and implement experiments to compare proposed work with SOTA baselines
• Publish research findings in high-impact journals and conferences
• Communicate and present research findings at international academic gatherings
• Create, maintain, and document high-quality research code for reproducibility
• Maintain good practice in managing and accessing sensitive medical datasets
• Assist the supervisor in the preparation of grant applications (as appropriate)
• Collaborate with scientists within the NYU Global Network and in Abu Dhabi

Benefits

• Competitive terms of employment
• Housing and educational subsidies for children

What This Job Offers

• Career Level: Entry Level
• Industry: Web Search Portals, Libraries, Archives, and Other Information Services
• Education Level: Ph.D. or professional degree