Senior Research Scientist (Mechanical Engineering/Electrical Engineering/Computer Science)

ANGEL is seeking a highly motivated Senior Research Scientist in the area of green computing, with a focus on computing and networking system energy efficiency optimization. The postdoc will play a key role in advancing our research agenda on sustainable data canters and energy-aware computing, bridging system-level performance with energy consumption reduction.

Key Responsibilities:

• Lead and conduct advanced research in the application of AI and Digital Twin technologies for data centre optimisation.

• Design methodologies for high-fidelity simulation models for data centre environments, including Computational Fluid Dynamics (CFD) for thermal analysis and energy simulation for consumption modelling.

• Design, train, and implement advanced machine learning and deep learning algorithms for predictive maintenance, anomaly detection, and real-time operational optimisation.

• Spearhead the design, development, and deployment of a Proof-of-Concept (PoC) system to validate research findings in a lab or live data centre environment.

• Analyse complex datasets from various data centre systems (e.g., BMS, DCIM, IoT sensors) to derive actionable insights.

• Publish research outcomes in top-tier international journals and present findings at leading academic conferences.

• Collaborate closely with industry partners, faculty members, and other researchers to ensure project goals are met.

• Contribute to writing research proposals for new funding opportunities.

• Provide guidance and mentorship to junior researchers and PhD students involved in the project.

Requirements:

• PhD degree in Mechanical Engineering, Electrical Engineering, Computer Science, or a related discipline.

• A strong, proven track record of high-quality publications in relevant fields.

• Proven expertise in developing high-fidelity models for complex environments, requiring advanced proficiency in CFD simulation for thermal management (e.g., Ansys Fluent, OpenFOAM) and/or energy performance modeling (e.g., EnergyPlus, IESVE).

• Solid theoretical and practical knowledge of machine learning and AI, including experience with frameworks like TensorFlow or PyTorch.

• Hands-on experience in building and validating Proof-of-Concept (PoC) systems.

• Strong programming skills in languages such as Python.

• Excellent analytical, problem-solving, and critical thinking abilities.

We regret that only shortlisted candidates will be notified.

Hiring Institution: NTU