Publisher
source

Birmingham City University

Smart Cities, AI, Urban Sustainability Birmingham City University in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

This is a fully funded 36-month PhD studentship at Birmingham City University, UK, offering a £20,780 tax-free annual stipend plus full tuition coverage.

Deadline

Expired

Country flag

Country

United Kingdom

University

Birmingham City University

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Keywords

Computer Science
Environmental Science
Electrical Engineering
Information Technology
Deep Learning
Smart Grid Technology
Predictive Modeling
Statistical Analysis
Artificial Intelligence
Urban Planning
Energy Engineering
Internet Of Things
Smart Cities
Urban Ecology
Urban Geography
Statistic
Digital Twins

About this position

I will be co-supervising this fantastic funded PhD opportunity at Birmingham City University!
The research will explore cutting-edge technologies like Deep Learning and Digital Twins to create Positive Energy Districts, transforming cities into smart and sustainable energy hubs.
If you have a passion for smart cities, AI and urban sustainability, this is a unique opportunity to make a real-world impact. Feel free to reach out if you have any questions about the project!

PhDOpportunity AI SmartCities UrbanEnergy Sustainability SSG Smart Sustainable Green Cities

Funded PhD Opportunity at Birmingham City University, UK

I am pleased to announce a 36-month fully funded PhD Studentship (£20,780 tax-free stipend + full tuition) on:

Smart Urban Energy Systems: Integrating Deep Learning and Digital Twins for Positive Energy Districts

This research will combine Deep Learning, Digital Twins, and real-time energy data to help transforming cities into positive energy hubs.

Entry Requirements:
·       Master’s degree in Computer Science, IT, AI, Data Science, or computing related fields
·       Proven skills in Deep Learning (CNNs, GNNs, DRL) and Python programming
·       Experience or strong interest in Digital Twins, IoT data, and real-time system simulation
·       Ability to work with large-scale data, predictive modelling, and statistical analysis
·       Knowledge of energy systems, optimisation, or urban analytics is a plus

Desirable Candidate:
·       Hands-on experience with Digital Twin platforms, simulation tools, or urban energy modelling
·       Published or presented work in AI, smart cities, or energy systems
·       Passion for applying AI to real-world sustainability challenges

Location: Birmingham City University
Start Date: 2nd February 2026
Deadline: 17th September 2025
Apply Here: https://lnkd.in/egCYNHk9

Supervisors: Dr. Syed Attique Shah (main), Dr Vahid Javidroozi (co-supervisor), Muhammad Ajmal Azad (co-supervisor)

If you are passionate about AI, Machine Learning, Deep Learning, digital innovation, and building sustainable cities, I would love to hear from you.

Enquiries: [email protected] (subject: “PhD studentship: SMARTPED”)

Please note that applications will only be accepted via the official application process. Kindly submit your application through the provided link, as applications sent via email will not be considered.
Apply Here: https://lnkd.in/egCYNHk9

PhDOpportunity
PhD
AI
DeepLearning
DigitalTwin
PositiveEnergyDistricts
NetZero
EnergyInnovation
SmartCities

Funding details

This is a fully funded 36-month PhD studentship at Birmingham City University, UK, offering a £20,780 tax-free annual stipend plus full tuition coverage.

What's required

Applicants must hold a Master’s degree in Computer Science, IT, AI, Data Science, or a closely related computing field. Proven skills in Deep Learning (CNNs, GNNs, DRL) and Python programming are required. Experience or strong interest in Digital Twins, IoT data, and real-time system simulation is expected. Candidates should be able to work with large-scale data, predictive modelling, and statistical analysis. Knowledge of energy systems, optimisation, or urban analytics is a plus. Desirable candidates will have hands-on experience with Digital Twin platforms, simulation tools, or urban energy modelling, and have published or presented work in AI, smart cities, or energy systems. A passion for applying AI to real-world sustainability challenges is highly valued.

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Professors

Senior Lecturer/Assistant Professor | PhD | CITP | PGCert (Ed) | FHEA | IEEE Senior Member | MBCS | World's Top 2% Scientists (Stanford University and Elsevier) | Global Talent UK | Programme Leader at BCU, UK |

University Name
Country flag

United Kingdom

Research Interests

Internet Of Things

Artificial Intelligence

Information Technology

Computer Science

Smart Grid Technology