Postdoctoral Researcher (Wellington NZ or remote)

Qualifications: PhD in Artificial Intelligence, Machine Learning, Computer Science, or a related discipline

Term: One-year, full time, fixed-term position

Start date: 15 October 2026

Location: Wellington or remote (International applicants are encouraged to apply)

About Us

Bodeker Scientific is an independent research organisation, recognised domestically and internationally for its expertise in atmospheric and climate research. The company conducts original scientific research through contracts held with both national funding agencies and international organisations. The company operates as a federation of largely independent researchers who collaboratively work on shared contracts under a commonly agreed company constitution. We focus on conducting high quality research within the time and financial constraints imposed by our research contracts. To achieve this goal, decision-making in the company is participatory with an emphasis on personal responsibility.

Role Description

We are seeking a post-doctoral researcher to support the development of intelligent, adaptive façade systems for climate resilient and energy-efficient buildings. The role will focus on designing, developing, implementing, and validating machine-learning models and control algorithms for the automated, real-time operation of dynamic building shading systems.

The research will use existing building-performance simulation data and multi-objective optimisation results to train and validate machine-learning models and control policies. These will support computationally efficient, real-time façade operation that maintains indoor environmental quality (e.g. occupant comfort) while minimising operational energy use.

A central component of the role will be developing control strategies that can respond appropriately when an occupant specifies a desire for a different environmental state. Following an occupant’s expressed desire for more/less light, warmer/colder conditions, reduced glare etc., the control system will use real-time sensor measurements, system feedback, and an independently developed control policy to identify the next-best feasible action or sequence of actions to change the façade configuration. This will guide the façade back towards energy-efficient operation and the required indoor environmental quality targets without requiring a complete online optimisation process at every control step.

Key Responsibilities

• Develop and validate machine-learning models (e.g. artificial neural networks) and control algorithms using simulation-generated data and multi-objective optimisation results to assess façade performance in terms of thermal conditions, airflow, daylight, glare, and energy use under different façade configurations and operating conditions.
• Develop and evaluate control strategies for selecting appropriate façade configurations under changing environmental and operational conditions.
• Design control methods that respond to occupant input and guide the façade back towards optimised operation.
• Integrate real-time sensor data and system feedback into closed-loop control and automation processes.
• Assess the accuracy, robustness, computational efficiency, and real-time suitability of the developed models and control methods.
• Contribute to technical documentation, research publications, presentations, and project reporting.

Essential Skills

• Strong knowledge of machine-learning methods, including artificial neural networks, deep learning, and reinforcement learning.
• Experience with developing machine-learning models for dynamic systems and applying them within optimisation or control frameworks.
• Understanding of sequential decision-making, feedback control, closed-loop system operation, and real-time control.
• Proficiency in Python and relevant scientific-computing and machine-learning libraries, such as PyTorch, or TensorFlow.
• Ability to evaluate model performance, identify overfitting, quantify uncertainty, and assess the generalisation of models to previously unseen operating conditions.
• Ability to write clear technical documentation and communicate research methods and results effectively.
• Ability to work collaboratively within a multidisciplinary research and development team.
• Familiarity with GitHub, or equivalent version-control and collaborative software-development tools. 

Why Join Us?

• Contribute to the development of sustainable and high-performance building technologies.
• Work within a collaborative, multidisciplinary, and inclusive research environment.
• Access professional-development opportunities through research, publication, conference participation, and international collaboration.
• Benefit from flexible working arrangements, noting that for this project you will be working remotely.
• Use advanced computational tools to support your work.
• Join a supportive team that values innovation, intellectual curiosity, humility, and continuous learning

Learn more and apply here: https://www.bodekerscientific.com/vacancies/post-doctoral-researcher