Postdoctoral Associate in Healthcare AI and Machine Learning
Join NYU Abu Dhabi’s Clinical Artificial Intelligence Lab to advance ML methodologies for patient diagnostics and prognostics.
Best for:Best for AI researchers with a PhD in machine learning, strong Python/PyTorch skills, and experience in healthcare data or multi-modal learning.
Overview
This postdoctoral position at NYU Abu Dhabi’s Clinical Artificial Intelligence Lab focuses on developing innovative machine learning techniques to improve healthcare outcomes. The successful candidate will collaborate with Dr. Farah Shamout and contribute to cutting-edge research on multi-modal learning, foundation models, and federated learning using large-scale medical datasets. The role involves designing experiments, publishing high-impact research, and mentoring junior researchers while engaging with global collaborators. Ideal for AI researchers passionate about bridging computational science and healthcare applications.
What you'll do
- Develop and implement ML methodologies to advance healthcare applications using large medical datasets (e.g., EHRs, medical images).
- Design and execute experiments to compare proposed research with state-of-the-art baselines and publish findings in top-tier journals/conferences.
- Collaborate with supervisors, PhD students, and undergraduate assistants to refine research agendas and mentor junior researchers.
- Maintain high-quality, reproducible research code and ensure ethical handling of sensitive medical data.
- Assist in grant applications and engage with NYU’s global network and local UAE medical institutions.
- Present research at international conferences and participate in NYU Abu Dhabi’s postdoctoral council and career development initiatives.
- Develop a personalized training plan to transition toward independent research careers.
Requirements
Degree required: PhD, MD/PhD, DPhil, or equivalent terminal degree in machine learning, artificial intelligence, computer science, mathematics, or related technical field (completed within the last 5 years).
Language: English (proficiency required for academic communication and collaboration).
Instruction: English
Publications: First-author peer-reviewed publication(s) or papers under review.
- Proven expertise in machine learning, particularly multi-modal learning, transfer learning, or foundation models.
- Strong programming proficiency in Python with experience using PyTorch/TensorFlow and maintaining code on GitHub.
- Experience running GPU-based experiments and managing large-scale medical datasets (e.g., EHRs, medical images).
- First-author peer-reviewed publication(s) or papers under review in AI/ML.
- Ability to visualize experimental results and learning curves effectively.
- Excellent written and oral communication skills for academic presentations and grant writing.
- No more than 5 years since completing the doctoral degree.
- Emirati candidates are encouraged to apply (in line with UAE regulations).
Funding & terms
How to apply
Deadline: 2026-11-15 · open until filled
Submit a cover letter, CV with full publication list, 1-page research statement, 1-page project proposal summary, transcript/degree certificate, and three letters of reference—all in PDF format. Email all documents to the supervisor directly.
- Cover letter
- CV with full publication list
- 1-page research statement
- 1-page project proposal summary
- Transcript or degree certificate
- 3 reference letters
Contact
Farah Shamout· Supervisor
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