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Computer Science and Engineering● OpenPostdoc⏰ 0 days leftOpen until filledPreview

Post-Doctoral Associate in Electrical and Computer Engineering

Join the Clinical Artificial Intelligence Lab at NYU Abu Dhabi to develop innovative machine learning methodologies for healthcare applications.

Best for:Best for machine learning researchers with a strong background in healthcare AI and experience managing large medical datasets.

New York University Abu Dhabi · Abu Dhabi, United Arab Emirates · R2 · Recognised researcher
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This is a postdoc position — not a PhD studentship.
Deadline
Until filled
rolling
Funding
Salaried
Competitive
Start date
flexible
Permanent
Location
Abu Dhabi
United Arab Emirates

Overview

The Clinical Artificial Intelligence Lab at NYU Abu Dhabi is seeking a Postdoctoral Researcher to advance machine learning methodologies for healthcare. The successful candidate will work with large-scale real-world datasets, including electronic health records and medical imagery, to improve patient diagnostics and prognostics. Reporting to Dr. Farah Shamout, the researcher will collaborate with a multidisciplinary team across the NYU global network and local UAE medical institutions. The role involves developing novel AI models, publishing high-impact research, and mentoring junior team members. Applicants should be passionate about the intersection of computing and medicine.

PostdocArtificial IntelligenceHealthcareDeep LearningElectronic Health RecordsComputational MedicineNYU Abu Dhabi

What you'll do

  • Develop and implement a research agenda focused on ML methodology for healthcare.
  • Design and execute experiments to compare proposed models against state-of-the-art baselines.
  • Publish research findings in high-impact academic journals and conferences.
  • Maintain high-quality, reproducible research code and documentation.
  • Manage and ensure the secure handling of sensitive medical datasets.
  • Mentor PhD students and undergraduate research assistants.
  • Assist in the preparation of grant applications and research proposals.
  • Collaborate with researchers across the NYU global network and local UAE institutions.

Requirements

Degree required: PhD, MD/PhD, or DPhil in Machine Learning, Artificial Intelligence, or a relevant technical field.

Language: English proficiency required.

Instruction: English

Publications: First-author peer-reviewed published papers (or under review).

Required skills
  • Strong proficiency in Python and deep learning frameworks like PyTorch or TensorFlow.
  • Demonstrated experience in managing and running experiments on GPUs.
  • Proven track record of first-author peer-reviewed publications.
  • Ability to maintain high-quality code repositories on GitHub.
  • Excellent oral and written communication skills.
  • Strong interpersonal skills for team-based research.
Nice to have
Deep knowledge of multi-modal learning, transfer learning, and self-supervised learning.Experience working with large-scale medical datasets such as EHR or medical images.Familiarity with high-performance computing (HPC) clusters.
Eligibility
  • Must have completed a doctoral degree within the last 5 years.
  • Emirati candidates are encouraged to apply in line with local regulations.

Funding & terms

Type
Salaried
Amount
Competitive
Duration
Not specified
Programme
New York University Abu Dhabi
New York University Abu Dhabi

How to apply

Deadline: 2026-10-15 · open until filled

Submit a cover letter, CV with publication list, 1-page research statement, 1-page project proposal summary, degree transcripts, and three reference letters in PDF format. Direct any inquiries to Dr. Farah Shamout via email.

Documents required
  • CV
  • Cover letter
  • Research statement
  • Project proposal summary
  • Degree transcripts
  • 3 reference letters
✉Apply by email

Contact

Farah Shamout· Principal Investigator

farah.shamout@nyu.edu

https://nyuad.nyu.edu/en/

FS
Prof.
Farah Shamout
Division of Engineering
Lab
Clinical Artificial Intelligence Lab
New York University Abu Dhabi
United Arab Emirates
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