Senior Research Fellow in AI Integration for Knitted Sensing and Energy Harvesting Systems

We seek a Senior Research Fellow (3–5 years postdoctoral experience) to serve as the systems integrator within an active research programme in knitted functional textiles. The postholder will work in close partnership with experimental colleagues across knitted sensor arrays and piezoelectric/triboelectric energy harvesting, developing deep technical understanding of both systems and building the AI platform that unifies them into an efficient, real-time wearable architecture.

Key Responsibilities

• Embed with the experimental research team to develop working knowledge of knitted sensor array behaviour and triboelectric/piezoelectric energy harvesting outputs, gaining the physical intuition required to build effective AI systems around them.
• Design and develop an AI/ML platform for real-time fusion of sensor data and energy harvesting output, enabling adaptive and energy-aware data acquisition from textile-based wearable systems.
• Build adaptive algorithms that dynamically optimise data collection, processing, and transmission relative to the available harvested energy budget, accounting for the irregular, low-frequency signal environment of knitted textile systems.
• Develop efficient edge inference pipelines suited to low-power wearable deployment, translating platform capabilities into demonstrable prototypes in collaboration with fabrication and electronics teams.
• Act as the technical bridge between sensing, energy harvesting, and AI sub-teams — translating domain knowledge across groups, facilitating design decisions, and maintaining system-level coherence across the research programme.
• Lead dissemination through high-impact journal publications and conference presentations, and contribute to grant reporting and future funding proposals.

Requirements

• PhD in Electrical Engineering, Computer Science, Materials Informatics, or a closely related discipline.
• 3–5 years of postdoctoral research experience with a strong publication record.
• Demonstrated expertise in machine learning for time-series or multimodal sensor data; experience with embedded systems or edge AI (TinyML, microcontroller deployment) is highly desirable.
• Familiarity with piezoelectric or triboelectric energy harvesting mechanisms, and/or experience working with electronic textiles or wearable sensing systems, is a significant advantage.
• Ability to listen, synthesise, and translate technical knowledge across domains — bridging experimental materials science, electronics, and AI within a collaborative, cross-disciplinary team.
• Ability to work independently and provide leadership to junior researchers and PhD students, with a track record of driving integration across multi-disciplinary teams.
• Excellent written and oral communication skills in English.

About the Position

This is a full-time, 2-year position embedded in a flagship initiative on wearable-embedded embodied AI for healthy ageing and rehabilitation. The postholder will serve as the integrating layer within a tripartite collaboration spanning advanced fibre design, knitted structure engineering, and AI-driven signal processing — working directly across all three strands to ensure that sensing performance, energy availability, and data intelligence are developed as a coherent, unified system.