Publisher
source

-

Architecture, Urban Design, Energy Systems Not mentioned in

Degree Level

PhD

Field of study

Computer Science

Funding

This is a fully funded PhD position. Details on stipend amount and tuition coverage are not specified, but the position is described as fully funded.

Deadline

Expired

Country

Not mentioned

University

University Name
Social connections

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Keywords

Computer Science
Environmental Science
Urban Planning
Civil Engineering
Architecture
Built Environment
Urbanism
Energy Consumption
Optimisation
Data-driven Modeling
Distributed Energy
Machine learning

About this position

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I am seeking 1-2 motivated Ph.D. students to advance research on resilient built environments through an interdisciplinary lens that integrates architectural and urban design with distributed energy systems. This fully funded position will focus on data-driven design methods (including machine learning algorithms and optimization models), urban building energy modeling, and energy-sharing networks to support neighborhood resilience.
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• Master’s degree in Architecture, Computer Science, Civil/Architectural Engineering, or related fields (exception possible for bachelor’s with strong research experience)
• Background or strong interest in computational design, AI/ML, optimization, energy modeling, or urban systems
• Proficiency in programming (Python required; C++ a plus)
Additional information is provided in the attached document.
Prospective applicants should submit the application of interest via Google Form: https://lnkd.in/gRVsSPEv

Funding details

This is a fully funded PhD position. Details on stipend amount and tuition coverage are not specified, but the position is described as fully funded.

What's required

Applicants should have a Master’s degree in Architecture, Computer Science, Civil/Architectural Engineering, or related fields. Exception is possible for candidates with a bachelor’s degree and strong research experience. Candidates should have a background or strong interest in computational design, AI/ML, optimization, energy modeling, or urban systems. Proficiency in programming is required (Python mandatory; C++ is a plus).

How to apply

Submit your application of interest via the provided Google Form link. Review the attached document for additional information. Ensure you meet the stated requirements before applying.

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