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Shayan Mirzabeigi

2 months ago

Graduate Research Assistant (MS/PhD) in Sustainable Construction Management and Building Science State University of New York College of Environmental Science and Forestry in United States

Degree Level

Master's, PhD

Field of study

Computer Science

Funding

The position is fully funded, providing full financial support for the selected M.S./Ph.D. graduate assistant. Details on stipend amount and tuition coverage are not specified.

Deadline

Expired

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Country

United States

University

SUNY College of Environmental Science and Forestry

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Where to contact

Official Email

Keywords

Computer Science
Machine Learning
Environmental Science
Mechanical Engineering
Deep Learning
Civil Engineering
Computer Vision
Architecture
Building Science
Sustainable Construction
Sensing Technologies
Energyplus
Building Energy Simulation

About this position

The Sustainable and Resilient Built Environment Lab (SARBEL) at the State University of New York College of Environmental Science and Forestry (SUNY ESF) is seeking a graduate research assistant (M.S./Ph.D.) to join their team in the field of sustainable construction management and building science. The selected student will work on research topics related to smart, sustainable built environments, with a focus on civil engineering, building science, and the application of advanced computational methods such as machine learning, computer vision, and building performance simulation.

Applicants should have a strong academic background in Civil Engineering, Building and Architectural Engineering, Building Science, Construction Engineering and Management, Mechanical Engineering, Computer Science or Engineering, or related fields. Experience with programming languages such as Python, MATLAB, or C/C++ is required. Additional skills in computer vision, deep learning, building simulation (e.g., EnergyPlus), and sensing technologies are highly valued. International applicants must meet English language requirements (TOEFL iBT 90 or IELTS 7) and all SUNY ESF Graduate School admission standards.

The position is fully funded, offering full financial support for the duration of the graduate program. Preference is given to applicants currently in the U.S., but international candidates are also encouraged to apply. The application deadline is February 15, 2026, with ongoing review of applications. To apply, candidates should email their CV and a one-page research interest statement to Dr. Shayan Mirzabeigi, Assistant Professor at SUNY ESF, at [email protected]. For more information about the lab and research focus, visit the SARBEL website or Dr. Mirzabeigi's faculty page.

This opportunity is ideal for students interested in sustainable construction, smart buildings, and the integration of advanced computational tools in the built environment. SUNY ESF is a leading institution in environmental science and forestry, providing a collaborative and innovative research environment for graduate students.

Funding details

The position is fully funded, providing full financial support for the selected M.S./Ph.D. graduate assistant. Details on stipend amount and tuition coverage are not specified.

What's required

Applicants must have a strong academic record and a background in Civil Engineering, Building and Architectural Engineering, Building Science, Construction Engineering and Management, Mechanical Engineering, Computer Science or Engineering, or related fields. Computer programming experience (e.g., Python, MATLAB, C/C++) is required. Experience in computer vision, machine learning, deep learning, building performance simulation (e.g., EnergyPlus), and/or sensing technologies is preferred. International students must have a TOEFL iBT score of at least 90 or an IELTS overall band of 7. Additional admission standards of the SUNY ESF Graduate School must be met. Preference is given to applicants currently in the U.S., but international applications are also considered.

How to apply

Email your current CV and a one-page description of your research interests and experience to [email protected] with the subject 'Prospective MS/PhD Student - Fall 2026'. Applications are reviewed as received. Only shortlisted candidates will be invited for an interview.

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