Postdoctoral Associate in Machine Learning, MBZUAI, Abu Dhabi, UAE

Postdoctoral Associate in Machine Learning: Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) invites applications for a Postdoctoral Associate position focused on advancing efficient machine learning and distributed learning. This role offers an opportunity to work in a dynamic and collaborative research environment at a globally recognized AI university located in Abu Dhabi, UAE.

Postdoctoral Associate in Efficient and Distributed Machine Learning


Designation: Postdoctoral Associate

DetailsInformation
Research AreaEfficient Machine Learning and Distributed Learning
LocationAbu Dhabi, UAE
Eligibility/QualificationPh.D. in Computer Science, Electrical Engineering, Applied Mathematics, or a related field
Application DeadlineJune 30, 2026 at 11:59 PM Eastern Time

Job Description:

As a Postdoctoral Associate, you will contribute to the theoretical foundations and practical implementations of scalable AI systems. Your key responsibilities will include:

  • Designing and implementing novel algorithms for scalable, efficient, and decentralized training of machine learning models.
  • Conducting theoretical research on optimization, generalization, or communication-constrained learning.
  • Translating theoretical insights into practical methods deployable in real-world settings.
  • Publishing in top-tier conferences and journals (e.g., NeurIPS, ICML, ICLR, COLT, JMLR).
  • Contributing to open-source software and reproducible research pipelines.
  • Mentoring graduate students and collaborating across interdisciplinary teams.

Qualifications:

Minimum Requirements:

  • Strong publication record in machine learning, optimization, or distributed systems.
  • Proficiency in deep learning frameworks such as PyTorch, TensorFlow, or JAX.
  • Solid programming skills and analytical thinking.
  • Effective written and verbal communication skills.

Preferred Qualifications:

  • Demonstrated ability to bridge theory and practice in scalable ML.
  • Experience with federated learning, quantization/pruning, or systems-level ML design.
  • Familiarity with topics such as stochastic optimization, communication-efficient algorithms, or model compression.
  • Previous mentorship experience or collaborative research across domains.

How to Apply:

Interested candidates should submit the following documents:

  1. Cover Letter
  2. Curriculum Vitae (C.V.)
  3. A link to your Google Scholar profile
  4. A 1–2 page research statement outlining directions you would like to pursue in efficient or distributed machine learning (optional)

Applications will be reviewed on a rolling basis, and the position will remain open until filled.

For more information or to apply, please visit MBZUAI Careers.


Last Date for Apply: June 30, 2026 at 11:59 PM Eastern Time

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