A fully funded PhD Graduate Assistantship is available for Fall 2026 at Virginia Tech’s Myers-Lawson School of Construction (MLSoC), focusing on Construction 4.0, building energy performance, and digital twins for the built environment under the supervision of Dr. Ashit Harode.

Overview of the PhD Graduate Assistantship

This position is a fully funded PhD graduate assistant role in the Myers-Lawson School of Construction at Virginia Tech, starting in Fall 2026. The successful candidate will join the Environmental Design and Planning (EDP) PhD program, which prepares researchers and industry leaders to tackle challenges across the lifecycle of the built environment.

The assistantship combines tuition support with a stipend in exchange for research responsibilities, allowing the student to focus on high-impact work in construction automation, energy performance, and digital twins. The selected student will be embedded in a research-intensive environment with access to cross-disciplinary collaborations across construction engineering, building science, and advanced digital technologies.

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Research Themes and Topics

The position centers on research at the intersection of Construction 4.0 technologies, building energy analytics, and next-generation digital representations of facilities. Work will align with several core themes:

Construction process automation and Construction 4.0 adoption in real projects, including advanced use of BIM, machine learning, and automated decision support.
Building energy analysis and performance evaluation across design, construction, and operation phases to support high-performance, energy-efficient buildings.
Digital twins for the built environment, leveraging data streams, BIM, and knowledge graphs to represent and optimize facilities continuously.
Construction research-to-application, emphasizing strong links with industry partners and the translation of research prototypes into practical tools and workflows.

Students can expect to work with concepts such as supervised and reinforcement learning for automation, graph-based ontologies for digital twins, and data-driven building performance diagnostics, which align with Dr. Harode’s prior research portfolio.

About the Advisor: Dr. Ashit Harode

Dr. Ashit Harode will join MLSoC as an assistant professor in August 2026 and will supervise the PhD graduate assistant. His research background spans Building Information Modeling (BIM), digital twins, and machine learning applications for construction automation and facility management.

He completed a PhD in Environmental Design and Planning at Virginia Tech, focusing on machine-learning-driven clash resolution and digital facility management workflows. Dr Harode has also worked as a BIM specialist in the LaGuardia Redevelopment Project, contributing practical experience in large-scale, complex construction environments. This blend of academic and industry experience creates a mentoring environment that emphasizes both rigorous research and real-world deployment.

Position Responsibilities

The successful PhD graduate assistant will be expected to contribute to multiple aspects of the research program and broader academic community.

Key responsibilities include:

Conducting original research in construction process automation, building energy performance analytics, and digital twin development for buildings and infrastructure.
Leading or supporting the design, implementation, and validation of computational tools, models, and workflows that can be adopted by industry partners.
Coauthoring peer-reviewed journal and conference papers and presenting findings at leading venues in construction management, computing, and building performance.
Participating in collaborative projects that bridge academia and industry, including case studies, pilot deployments, and demonstration projects.
Supporting proposal development and contributing to competitive grant applications related to Construction 4.0 and digital built-environment technologies.

As part of the Environmental Design and Planning PhD program, the student will also take coursework, participate in seminars, and engage with a multidisciplinary cohort focusing on the future of the built environment.

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Requirements for Digital Twins Position

This assistantship targets applicants with a strong foundation in construction, civil engineering, or related disciplines, particularly those who want to specialize in computational and data-driven methods.

Minimum expectations include:

A master’s degree in civil engineering, construction engineering/management, or a closely related field by the time of enrollment in fall 2026.
Strong academic performance and evidence of research capability, such as a thesis, project work, or publications.
Ability to work independently and collaboratively on research projects with both academic and industry stakeholders.

The call explicitly notes preference for applicants with experience in one or more of the following areas:

Machine learning and applied AI, especially in construction, built environment analytics, or engineering contexts.
Energy modeling and building performance analysis, including the use of simulation tools or performance monitoring data.
Building Information Modeling (BIM) software and workflows for design, coordination, and facility management.
Digital twin development or closely related digital built environment platforms.
Publication of peer-reviewed journal or conference articles in construction management, building performance, or related domains.

Because the role sits within a U.S. doctoral program, applicants must also meet Virginia Tech Graduate School admission requirements, including submission of transcripts, English language proficiency documentation (for international students), and a complete online application.

Application Materials for Digital Twins PhD

Interested candidates must compile a set of application materials that demonstrate fit, motivation, and research potential for the position.

The call specifies the following documents:

Cover letter (maximum 1 page) highlighting your fit with the position, focusing on your background in Construction 4.0, BIM, energy analysis, and/or digital twins.
Curriculum vitae (CV) summarizing education, research, technical skills, publications, and professional experience.
Statement of Purpose (1 page) describing your achievements, PhD motivation, long-term goals, and how you intend to contribute to the construction industry.
An official GRE score report, with a quantitative score of at least 155 or above, is indicated in the call.
Two letters of recommendation or contact information for referees who can speak to your academic and research potential.

Applicants should ensure these materials clearly articulate their experience in areas such as machine learning, BIM, building performance, and digital workflows, as these align closely with the advisor’s research agenda.

Apply Here: Contact and Submission Link

The announcement instructs applicants to email Dr. Ashit Harode with their application package and to follow Virginia Tech’s graduate application procedures.

Apply for the Digital Twins PhD Graduate Assistantship by

Preparing the required documents (cover letter, CV, statement of purpose, GRE score report, and referee details).
Submit a formal application to the Virginia Tech Graduate School using the online system: https://graduateschool.vt.edu/admissions/how-to-apply.html.
Email Dr. Ashit Harode at the address listed in the call (subject line typically indicated as “PhD Application”) with your materials attached and a brief message summarizing your interests and background.

For general information about the Environmental Design and Planning PhD program within MLSoC, prospective students can also review the program page: https://mlsoc.vt.edu/programs/graduate/doctor-of-philosophy-in-environmental-design-and-planning.html.

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Why Choose Virginia Tech and Digital Twins

Virginia Tech is a leading research university with a strong focus on the built environment and an ethos of applying knowledge to practice. The Myers-Lawson School of Construction’s Environmental Design and Planning PhD program is explicitly structured to foster cross-disciplinary research across building design, construction, operations, and end-of-life, aligning well with the convergence of construction automation and digital technologies highlighted in this assistantship.

Students in the program learn from faculty engaged in cutting-edge work on BIM, energy-efficient design, green materials, construction waste management, and urban resilience. This creates a fertile ecosystem for high-impact research into Construction 4.0, digital twins, and AI-based automation and offers strong career pathways in academia, industry R&D, and advanced digital practice in the architecture, engineering, construction, and operations (AECO) sector.