Research Assistant (RA)

Job Description

About the Project

The Agentic AI Maximo Platform Project is a pioneering initiative led by the College of Engineering and IT at the University of Dubai, in collaboration with the Islamic Affairs and Charitable Activities Department (IACAD).
The project enhances the IBM Maximo Application Suite by integrating an Agentic AI layer, transforming Maximo modules into autonomous, explainable agents that collaborate for predictive maintenance, fraud detection, budget forecasting, and intelligent resource allocation across more than 1,000 facilities in Dubai.

Role Overview

The Research Assistant (RA) will play a vital role in developing and validating AI-driven agentic modules within the IBM Maximo ecosystem.
This position is ideal for candidates passionate about AI systems design, machine learning for operations automation, and multi-agent systems.
The RA will work under faculty supervision, collaborating with data scientists, software engineers, and industry partners to deliver research-grade innovations and deployable AI solutions.

Key Responsibilities

• Agentic Intelligence Development: Design and evaluate learning algorithms for Maximo agents (Predict, Fraud & Controls, Budget Intelligence, Scheduling), integrating reinforcement learning and human-in-the-loop feedback loops.
• AI Model Design and Optimization: Develop predictive models for failure detection, asset health scoring, and budget forecasting using methods such as Gradient Boosting, LSTM, Prophet, and XGBoost.
• Data Integration and Feature Engineering: Prepare and integrate IoT, telemetry, and financial data streams through Maximo’s Integration Framework (MIF) and Collaboration Bus.
• Explainable AI and Governance: Implement interpretable AI models, monitor bias and drift, and support explainability dashboards for decision transparency.
• Continuous Learning Pipelines: Establish retraining loops triggered by performance KPIs (MAPE, precision, SLA compliance) and operational feedback from Maximo interfaces.
• Research Output and Dissemination: Contribute to publications, technical deliverables, and reports on AI automation, multi-agent architectures, and generative AI workflows.

Required Qualifications

Educational Background:

• Master’s degree (PhD is a plus) in Artificial Intelligence, Computer Science, Data Science, Electrical/Computer Engineering, or a related field.

Technical Skills:

• Strong proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Experience in AI model deployment and automation pipelines.
• Familiarity with IBM Maximo or similar enterprise asset management systems is a plus.
• Knowledge of reinforcement learning, time-series forecasting, and anomaly detection.
• Experience working with IoT data, databases, and cloud platforms (AWS, Azure, or IBM Cloud).

Soft Skills:

• Strong analytical and problem-solving abilities.
• Excellent technical writing and communication skills.
• Ability to collaborate effectively with interdisciplinary teams.
• Motivation for applied AI research and publication in reputable journals.

Preferred Qualifications

• Hands-on experience with multi-agent systems, AI workflow orchestration, or intelligent automation frameworks.
• Prior experience with IBM Maximo, Digital Twins, or AI for facility management.
• Published research in machine learning, agentic AI, or predictive maintenance.

Why Join Us?

• Work on a cutting-edge national AI project transforming Dubai’s facility management ecosystem.
• Gain hands-on experience with IBM Maximo and enterprise AI systems.
• Collaborate with leading researchers and industrial partners (IACAD, IBM, and UD).
• Access advanced computing infrastructure and AI research tools.
• Opportunity to publish in top-tier conferences and journals.

Application Details

Applications will remain open until the position is filled.
Interested candidates should submit the following to the College of Engineering and IT, University of Dubai:

• A detailed CV highlighting relevant research experience.
• A cover letter explaining motivation and fit for the position.
• Academic transcripts (Master’s and/or PhD).

• Contact information of two references.

Expected Start Date: As soon as possible
Location: University of Dubai, Academic City, Dubai, UAE