The Building Performance Research Centre is always looking for talented, creative, and ambitious engineering students (of all disciplines) to perform innovative research projects. Our projects range from very hands-on to theoretical. See the Projects webpage for typical HBI Lab projects. If you are interested, please submit a current CV, transcript(s), and a sample of writing to Prof. O’Brien (liam_obrien@carleton.ca). For the first four projects, also CC Burak Gunay (burak.gunay@carleton.ca).

Specific positions include, but are not limited to:

  1. Systematic simplified energy modelling of building portfolio. Goal: Develop and apply workflow to convert building details into simplified models that can be systematically optimized to identify operations and retrofit opportunities.
  2. Visualization of building operational energy and impact of retrofits. Goal: Provide greater understanding of multi-scale building energy and GHG flows to key stakeholders (operators, tenants, policy/decision makers).
  3. Measurement and quantification of occupant building utilization. Goal: Identify opportunities for improved space utilization and quantify corresponding energy, GHG, and cost savings.
  4. Text-mining operator logbooks to develop preventive maintenance strategies. Goals: 1.Identify top work-order types and their occurrence frequencies; 2.Analyze how maintenance efforts are distributed in building clusters; 3.Analyze work-order intensities with archived sensor/meter data and look for symptoms in the sensor datasets; 4.Develop recommendations to optimize maintenance efforts.
  5. PhD: Development and testing of novel building controls techniques and field studies in the Health Sciences Building. 
  6. PhD: Design using occupant behaviour modelling and simulation. Use simulation to design and optimize novel building concepts to both reduce energy use and provide a more comfortable indoor environment.
  7. MASc or PhD: Field studies to observe/model occupant behaviour and comfort. Occupants have fascinating and often puzzling behaviours that can only be properly assessed through field studies. This position entails designing an experiment to monitor -directly or indirectly- occupants and their interaction with buildings (e.g., blinds, windows, thermostats, lighting, equipment, etc.) to contribute to the ever-growing field of occupant behaviour modelling and simulation.

8. PhD for development and testing of new fault detection, diagnostics, and prognostics methodologies for commercial building systems

The project will target the development and testing of new fault detection, diagnostics, and prognostics methodologies for commercial building systems. Students with a background in building engineering or related areas (mechanical engineering, systems and computer engineering, electrical engineering, engineering physics) and knowledge of building modelling techniques and HVAC systems are encouraged to apply. Familiarity with machine learning and data science, including statistical inference and classification and regression models is a strong asset. Programming experience (R, Python, Matlab, etc.) is an advantage. If interested, please contact Burak Gunay at burak.gunay@carleton.ca.