Publisher
source

Ariel University

PhD Positions: AI‑Powered Urban Digital Twins for Data‑Driven Cities (METROPOLIS Project) Ariel University in Israel

Degree Level

PhD

Field of study

Computer Science

Funding

Funded PhD Project (Students Worldwide)

Deadline

Year round applications

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Country

Israel

University

Ariel University

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Keywords

Computer Science
Information Technology
Geography
Artificial Intelligence
Urban Planning
Civil Engineering
Human-computer Interaction
Architecture
Built Environment
Digital Twin Technology
Internet Of Things
Urban Geography
Data Harmonization
Geospatial Information
Machine learning

About this position

The METROPOLIS project at Ariel University offers an exciting opportunity for three PhD researchers to advance the field of Urban Digital Twins (UDT) through AI-powered frameworks. Cities today face complex challenges in sustainability, climate resilience, energy efficiency, mobility, and social inclusion. Urban Digital Twins are virtual representations of cities that combine real-time data and predictive models, enabling evidence-based planning and governance. Despite their potential, current UDT implementations are limited by fragmentation and lack of scalability.

This project aims to develop an interoperable, AI-based UDT framework that can be rapidly deployed and adapted across diverse urban environments. The research will focus on integrating heterogeneous urban data sources, including geospatial, BIM, IoT, satellite, and administrative data, with advanced AI models. The goal is to create intuitive decision-support tools for planners, policymakers, and stakeholders. A major pilot deployment in Tel Aviv will validate the framework’s technical performance, usability, governance impact, and replicability.

PhD researchers will work on three core areas: GIS data harmonization and AI engine development, urban AI model creation, and user experience design. The project is housed in the Department of Architecture and is highly interdisciplinary, spanning architecture, urban planning, computer science, civil engineering, human-computer interaction, and urban geography. Candidates will collaborate with experts and stakeholders to address real-world urban challenges.

Applicants should have a strong academic background in a relevant field and demonstrate skills in AI, machine learning, GIS, or related areas. The position does not specify funding details, so candidates are encouraged to inquire directly. Applications are accepted year-round, and interested individuals should submit their CV, transcripts, and a cover letter via the project’s FindAPhD page. This is a unique opportunity to contribute to the future of smart, data-driven cities and gain expertise in cutting-edge urban technologies.

Funding details

Funded PhD Project (Students Worldwide)

What's required

Applicants should hold a relevant undergraduate or master's degree in architecture, urban planning, computer science, civil engineering, geography, or a related field. Experience or coursework in artificial intelligence, machine learning, GIS, geospatial data, or human-computer interaction is highly desirable. Strong programming and data analysis skills are preferred. English proficiency is required; additional language requirements are not specified.

How to apply

Interested candidates should apply online via the FindAPhD project page. Prepare a CV, academic transcripts, and a cover letter outlining your research interests and relevant experience. Contact the supervisor for further details if needed.

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