Post-Doctoral Associate in the Division of Engineering (Electrical and Computer Engineering)

The Clinical Artificial Intelligence Lab at the company aims to enhance patient care through the development of innovative machine learning methodologies tailored to unique computational challenges in healthcare. The lab utilizes extensive real-world datasets, including electronic health records and medical imaging, to improve patient diagnostics and prognostics.

We are seeking a Postdoctoral Researcher with strong machine learning capabilities and a deep interest in multidisciplinary research spanning computing and healthcare. Desired research methodologies include multi-modal learning, foundation models (including large language models), agentic AI, multi-agent AI systems, transfer learning, self-supervised learning, and federated learning.

The selected researcher will closely collaborate with Dr. Farah Shamout and other researchers, PhD students, and undergraduate assistants. Opportunities for collaboration also extend to campuses and various medical institutions within the UAE.

Key Responsibilities:

• Support the supervisor in the execution of research agendas.
• Conduct high-quality, innovative research with a primary focus on ML methodologies for healthcare.
• Generate novel high-impact ideas addressing current gaps in the state-of-the-art.
• Design and implement experiments to benchmark proposed methodologies against existing solutions.
• Publish findings in reputable journals and present at academic conferences.
• Maintain and document high-quality research code to ensure reproducibility.
• Handle sensitive medical datasets with care and maintain best practices.
• Assist in grant preparation as required.
• Engage with scientific communities within the company Global Network and Abu Dhabi.
• Attend professional development training and mentor students as appropriate.
• Create a personalized training and development plan in consultation with the supervisor.

Minimum Qualifications:

• Completion of a PhD, MD/PhD, DPhil, or equivalent from a recognized institution (must be within 5 years of graduation).
• Doctoral research experience in machine learning and artificial intelligence.
• Bachelor's or Master's degree in computer science, mathematics, computer engineering, or a related field.
• First-author publications in peer-reviewed journals (either published or under review).
• Proficiency in Python and relevant libraries (e.g., PyTorch, TensorFlow).
• Experience with version control (e.g., GitHub) and GPU experimentation.
• Strong data visualization skills.
• Excellent interpersonal and communication skills.
• Self-motivated with the ability to work both independently and collaboratively.

Preferred Qualifications:

• Experience in machine learning applications within healthcare.
• Knowledge of multi-modal learning, transfer learning, and self-supervised learning.
• Familiarity with large medical datasets and high-performance computing environments.

Application Process:
To apply, candidates must submit a cover letter, curriculum vitae (including a full publication list), a 1-page research statement, a 1-page project proposal summary, a transcript or degree, and three letters of reference, all formatted in PDF. For inquiries, please reach out to Prof. Farah Shamout at [email protected].

Compensation and Benefits:
The company offers competitive employment terms, which include housing and educational subsidies for children. Applications are accepted immediately and assessed until the position is filled.