Postdoctoral Researcher: AI, Federated Learning & XAI

Employment; Doha; On-site; QAR 218,000 - 328,000; Full time

Benefits offered by this job

Competitive salary

International collaborations

Professional development

Job summary

UDST seeks an outstanding Postdoctoral Researcher for the Center of Excellence in Artificial Intelligence and Innovation to advance applied AI research in healthcare, energy, and smart infrastructure. You will develop privacy-preserving ML, interpretable AI solutions, and deploy models on edge and cloud platforms with real-world impact.

PhD in CS/AI is required, with a strong publication record and experience in federated learning, XAI, or privacy-preserving ML.

Qualifications

• PhD in Computer Science, AI, ML or closely related field.
• Demonstrated research in ML with focus on federated learning, explainable AI, or privacy-preserving ML.
• Strong publication record in top AI/ML conferences/journals.
• Expertise in deep learning frameworks (PyTorch, Tensor Flow, Keras) and ML tools.
• Proven ability to conduct independent research and collaborate with teams.
• Excellent communication and technical writing skills.

Responsibilities

• Conduct applied research in ML, federated learning, and explainable AI for healthcare, energy, and smart infrastructure.
• Develop privacy-preserving ML systems and interpretable AI solutions.
• Deploy models on edge and cloud platforms with robustness and scalability.
• Publish findings in top-tier conferences and journals.
• Mentor junior researchers and contribute to proposals and funding applications.

Skills

English fluency

Independent research

Analytical skills

Presentation skills

Collaboration skills

Education

PhD in CS/AI

Tools

PyTorch

TensorFlow

Keras

scikit-learn

XGBoost

Git

Job description

UDST seeks an outstanding Postdoctoral Researcher for the Center of Excellence in Artificial Intelligence and Innovation to advance applied AI research in healthcare, energy, and smart infrastructure. You will develop privacy-preserving ML, interpretable AI solutions, and deploy models on edge and cloud platforms with real-world impact.

PhD in CS/AI is required, with a strong publication record and experience in federated learning, XAI, or privacy-preserving ML.