
Post-Doctoral Associate in the Division of Engineering - Dr. Farah Shamout
- أبو ظبي
- دائم
- دوام كامل
- Multi-modal learning
- Foundation models, including large language models
- Agentic AI
- Multi-agent AI systems
- Transfer learning
- Self-supervised learning
- Federated learning
- Research
- 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);
- And collaborate with scientists within the NYU Global Network and in Abu Dhabi.
- Attend trainings and workshops for career development;
- Mentor PhD students and undergraduate research assistants (as appropriate);
- Actively participate in events and committees at NYU Abu Dhabi, such as the Postdoctoral Council Steering Committee;
- Gain experience in applying for local research grants (subject to eligibility);
- And transition to independence to pursue a career of choosing following the appointment.
- The researcher will create a personalized training and development plan with the supervisor.
- 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
- 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
Times Higher Education