Start Date
Immediate
Expiry Date
04 May, 25
Salary
0.0
Posted On
04 Feb, 25
Experience
0 year(s) or above
Remote Job
No
Telecommute
No
Sponsor Visa
No
Skills
Machine Learning, Python, Data Science, Construction Management, Computer Science, Headsets, C++, Civil Engineering
Industry
Construction
DESCRIPTION
The S.M.A.R.T. Construction Research Group at NYU Abu Dhabi is seeking applications for an open-rank research position of a Post doctoral associate focused on advancing smart digital technologies to optimize construction and civil infrastructure projects. This position offers an exciting opportunity to lead and contribute to cutting-edge research in digital twins, immersive technologies (VR/AR/MR), data driven decision-making, and construction progress monitoring and tracking.
QUALIFICATIONS
Candidate must have the required degree PhD for Postdoc or equivalent in Civil Engineering, Construction Management, Computer Science, Data Science, or a related field. Expertise in digital twins, machine learning, and data visualization tools. Experience with immersive technologies (VR/AR/MR) and application development for headsets or similar devices. Strong programming skills in Python, C++, or similar languages, and experience with simulation frameworks. For those being considered for the postdoc position, a proven track record of publishing high-quality research and contributing to interdisciplinary projects.
Developing and implementing digital twin platforms and graphical user interfaces (GUIs) to support construction monitoring and decision-making. The role involves leveraging machine learning and data visualization techniques to analyze and track construction progress using diverse datasets, such as images, videos, and point clouds. Additionally, candidates will integrate immersive technologies, including virtual reality (VR), augmented reality (AR), and mixed reality (MR), to enable real-time visualization and interaction with project data. Research will be conducted and validated through simulations and real-world case studies, pushing the boundaries of construction automation and optimization.