Research Fellow, Built Environment

Updated: about 1 month ago
Job Type: FullTime
Deadline: 07 Aug 2022

Job Description

The focus of this position is the development of ML models for the Cozie Apple Project. There are large networks of Internet-of-Things (IoT) and AI-driven modelling technologies being installed in NUS through various research projects. The Internet-of-Things paradigm provides copious amounts of high-quality temporal data pertaining to indoor and outdoor environmental quality, comfort, and energy. However, a barrier to using IoT technologies is their lack of spatial context in the built environment. Adding the spatial and semantic information through the use of Building Information and Energy Models (BIM/BEM), and Geographic Information Systems (GIS) unleashes huge potential - the most promising being the automation of spatial context and location of fixed and wearable IoT. In this framework, IoT is put in the spatial and material context of real buildings on the NUS campus in a scalable way. Developing and training AI models to make predictions based on the data can have a strong impact in the areas of Occupancy Detection, Energy Systems Optimization, and Human Comfort and Wellness.

Job Requirements

Desired candidates should be familiar with the building and construction industry through previous experience in research design, project management or analysis of buildings. The position will require experience in temporal data analysis tasks such as supervised model  development,  unsupervised  clustering  analysis,  and  interpretation  of results. The job will require the assembly, commissioning, and deployment of a hardware and software visual analytics platform. The candidate will require a history of similar hardware/software implementations.

The candidate should have a Bachelor’s and Master’s degree in Engineering, Architecture, Computer Science or similar degree and should have a PhD in similar fields, or be nearing completion of a PhD degree. The candidate should be an expert in using Python, Pandas, Kaggle, Jupyter Notebooks, and advanced Machine Learning techniques.

Covid-19 Message

At NUS, the health and safety of our staff and students are one of our utmost priorities, and COVID-vaccination supports our commitment to ensure the safety of our community and to make NUS as safe and welcoming as possible. Many of our roles require a significant amount of physical interactions with students/staff/public members. Even for job roles that may be performed remotely, there will be instances where on-campus presence is required.

Taking into consideration the health and well-being of our staff and students and to better protect everyone in the campus, applicants are strongly encouraged to have themselves fully COVID-19 vaccinated to secure successful employment with NUS.

More Information

Location: Kent Ridge Campus
Organization: College of Design and Engineering
Department: The Built Environment
Employee Referral Eligible: No
Job requisition ID: 15257

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