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The Associate will be employed on a Knowledge Transfer Partnership (KTP) project between WeCare4Air Ltd and the University of Warwick (School of Engineering, BioSensors Lab).
The project will develop a new generation of innovative tools for environmental monitoring, designed for integration with Smart Cities, Smart Buildings and Smart Transport. The overarching aim is to deliver, real-time local air quality intelligence that supports improved public health and better operational decision-making. The system will combine measurement performance with an AI-enabled platform for long-term deployments with improved reliability.
The Associate will lead the design and implementation of a next-generation architecture for a reference-grade air quality analyser. Key technical responsibilities will include development of embedded/electronic systems, embedded/edge software, implementation of sensor fusion approaches, and deployment of AI methods to support, for example, predictive diagnostics, automated quality assurance.
Working primarily within WeCare4Air, the Associate will collaborate closely with engineering, product and customer-facing teams to ensure the solution is fit for purpose, deployable and supportable. Alongside core R&D delivery, they will contribute to requirements capture, test planning, verification/validation, and the creation of technical documentation and knowledge resources needed to embed the capability within the business.
The Associate will also maintain access to the BioSensors Lab at the University of Warwick, benefiting from academic supervision, access to research expertise, and support in evaluation methodologies and dissemination. The role is collaborative and will require effective engagement with a range of stakeholders, moving between research and commercial needs, managing milestones, and ensuring timely delivery of project outcomes.
This post is part of the KTP initiative funded by Innovate UK. Knowledge Transfer Partnerships is a UK-wide programme that has been helping businesses for the past 40 years to improve their competitiveness and productivity through the better use of knowledge, technology and skills that reside within the UK Knowledge Base. It is an exciting opportunity to work across industry and academia, applying cutting-edge research to deliver tangible impact.
The successful candidate will have a strong academic and technical foundation, complemented by excellent interpersonal and project management skills. You will hold a good honours degree (or equivalent experience) in Electronic Engineering, Computer Science, Embedded Systems or a closely related discipline, plus a postgraduate qualification (MSc/PhD) or industrial experience in embedded systems, AI/machine learning, digital signal processing or a relevant area.
You will be technically confident delivering end-to-end solutions spanning electronics, embedded/edge software, microcontrollers and connected systems. Essential skills include electronics knowledge, strong programming skills for data handling and model development/testing, and experience of software–hardware integration (sensor/instrument interfaces and system-level debugging, with knowledge of electronics). You should be comfortable working with real-time constraints (e.g., RTOS concepts), implementing data acquisition and processing pipelines, and applying signal processing methods to time-series sensor data. Familiarity with deploying AI/ML models (e.g., anomaly detection, drift detection, regression/classification) in practical setting. Knowledge of digital communications, device connectivity and the fundamentals of secure connected products (e.g., encrypted communications, authentication, update concepts) is also desirable.
In addition, it is desirable if your experience includes contributing to product development of field-deployed instrumentation, low-power or long-term unattended system design. Exposure to air quality monitoring and gas sensing (including calibration, cross-sensitivities and environmental compensation) would be advantageous but is not essential.
You will be self-motivated, adaptable and able to work effectively across industrial and academic environments, communicating technical ideas clearly and translating requirements into validated, deployable solutions.
Due to thirdhand smoke causing pollutants to linger on surfaces, skin, hair and clothing which could interfere with data quality, WeCare4Air are strictly a non-smoking company. Candidates must be non-smokers (including e-cigarettes and vaping).
For details on the experience and skills required, please refer to the job description attached as a PDF below.
This is an opportunity to join a collaboration between Warwick and WeCare4Air in developing the next generation of AI embedded reference analysers. The Associate will form part of WeCare4Air’s engineering/R&D team and will be primarily based at the company, working closely with the industrial supervisor with frequent day-to-day interaction to ensure delivery, progress and effective knowledge transfer. The project will require the Associate to work across laboratory development and real-world deployment contexts; therefore, independent travel will be expected between WeCare4Air, the University of Warwick, and pilot/customer or monitoring sites as required for testing and validation.
Hybrid working may be possible at times if approved by the supervisors. However, the work will mainly be carried out on-site due to the hands-on nature of instrumentation development, integration and field validation, with the Associate expected to be office/lab based for the majority of the working week (depending on project phase and deployment needs).
We Care 4 Air are committed to delivering high-quality solutions with a focus on data capture and customer satisfaction. The company provides global technical support, ensuring reliable data capture and exceptional service. Their customers include Environment Agencies, Local Authorities, Universities, and commercial organizations worldwide. Driven by a mission to enhance air quality, WeCare4Air consistently goes above and beyond to meet customer needs.
The Associate will become a member of the School of Engineering, at the University of Warwick. The School of Engineering is a broad department teaching all forms of Engineering. The position will be with the BioSensors Group in Engineering (http://www.warwick.ac.uk/go/bsl), which is internationally recognised for its work in gas sensors and olfaction, as well as developing instrumentation and units designed for monitoring air quality in consumer and industrial settings. The Associate will also receive academic supervision from the BioSensors Lab within the School of Engineering at the University of Warwick, with access to specialist expertise and facilities supporting rigorous evaluation and translation of research into a deployable solution.
The School of Engineering is committed to the principles of the Athena SWAN Charter, which recognises work undertaken to address gender equality, representation and progression for all staff working in an academic environment. The School currently holds the Athena SWAN Gold award, and the University holds an Institutional Silver award.
Further information about the work of the School in relation to Athena SWAN can be found at the following link: Athena SWAN - School of Engineering - University of Warwick
This post is part of the Knowledge Transfer Partnership (KTP) initiative funded by Innovate UK. Knowledge Transfer Partnerships is a UK-wide programme that has been helping businesses for the past 50 years to improve their competitiveness and productivity through the better use of knowledge, technology and skills that reside within the UK Knowledge Base. For further information visit http://ktp.innovateuk.org/
We are a world-leading research-intensive university founded in 1965. We are ranked 74th in the world and 9th in the UK.* Additionally, 92% of our research is rated world-leading or internationally excellent.**
Find out more about us at warwick.ac.uk/about/.
* World University Ranking 2026, Complete University Guide 2026
** Research Excellence Framework 2021
CLOSING DEADLINE: Sunday 21 June 2026 at 11:55pm (UK Time)
To apply, please click APPLY below and submit your application by the closing deadline.
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This opportunity is closed to applications.
