Research Assistant-AI Driven Disaster and Emergency Management System

Position Details

Position Information Job Title: Research Assistant-AI Driven Disaster and Emergency Management System Position Type: Student Division: Academic Affairs Department: Computer Science

Job Description Computer Science is seeking highly motivated undergraduate or graduate research assistants (GRA) to contribute to a cutting-edge interdisciplinary research project focused on developing an AI-enabled secure and interoperable disaster and emergency management platform. The project addresses critical challenges observed in large-scale disasters-such as delayed alerts, lack of coordination among agencies, and limited use of intelligent decision-support systems-by integrating knowledge graphs, explainable AI (XAI), real-time alerting, LLM-based interaction, and cybersecurity/privacy mechanisms.

Key Responsibilities

• Collect, preprocess, and manage heterogeneous data from sensors, system logs, policy documents, and open-source disaster datasets.
• Design and implement a unified knowledge graph-based data model for data integration and interoperability.
• Develop and evaluate AI/ML models tailored to different stakeholders (e.g., first responders, government agencies, researchers).
• Integrate Explainable AI (XAI) techniques to provide transparent and interpretable decision support.
• Contribute to the development of a real-time smart alert and communication system.
• Assist in building an LLM-based conversational interface for natural language interaction with the platform.
• Implement and evaluate security and privacy mechanisms for secure data sharing and system access.
• Participate in system testing using the TEEX Disaster City testbed and other benchmark datasets.
• Contribute to technical reports, research papers, presentations, and proposal development.

Required Qualifications

• Must be a currently enrolled student registered for classes in an undergraduate or graduate program in Computer Science, AI, Cybersecurity, Data Science, or a closely related field.
• Strong programming skills in Python.
• Knowledge of machine learning or deep learning.
• Familiarity with data structures, databases, and basic software development practices.
• Ability to work both independently and collaboratively in a research environment.

Preferred Qualifications

• Experience with knowledge graphs, graph databases, or semantic web technologies (e.g., RDF, SPARQL, Neo4j).
• Background in natural language processing, LLMs, or information extraction.
• Familiarity with XAI, cybersecurity, privacy-preserving methods, or distributed systems.
• Experience with cloud platforms, real-time data processing, or IoT data.
• Prior research experience and interest in publishing.

Physical Demands Salary: 15-20 hour

EEO Statement All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability, genetic information, or status as a protected veteran.

In compliance with the Americans with Disabilities Act (ADA), Angelo State University is committed to providing reasonable accommodations to ensure equal access to employment opportunities for qualified individuals with disabilities. We are committed to ensuring that a qualified individual with a disability has the same rights and privileges in employment as non-disabled employees. If an accommodation is requested for the job application process, please contact our office at 325-942-2168 or email us at hr@angelo.edu.

Posting Detail Information Posting Number: [Not Provided] Number of Vacancies: 1 Open Date: 03/18/2026 Close Date: Open Until Filled Yes

Special Instructions to Applicant In the "Other" application documents needed:

• Statement of research interest
• Optional Links to GitHub, publications, or prior projects

Questions Dr. Erdogan Dogdu: erdogan.dogdu@angelo.edu

Supplemental Questions Required fields are indicated with an asterisk.

Documents Needed To Apply Required Documents:

• Transcripts
• Unofficial Curriculum Vitae

Optional Documents:

• Cover Letter