Research Assistant [ML & hardware benchmarking for real-time acoustic monitoring of the environment]
About the role
If selected for this job as a research assistant, you will support the development and evaluation of low-cost, low-power, high-performance hardware and software for scalable, real-time passive acoustic monitoring of birds in the natural environment.
Your work will be carried out as part of an ESPRC-funded project in collaboration with the UK Centre for Ecology & Hydrology and WildSonic AI.
You will join the project for 1 day/week for 12 weeks during the final 3 months of the project.
You will focus on validation and benchmarking of the firmware, machine learning models, and hardware (e.g., by writing and using repeatable test scripts, conducting energy and latency measurement, comparing against existing open-source baselines, and collating results and partner feedback). On the way, you will learn about machine learning, embedded systems, and the path from a prototype to a product. You will work with the partners to demonstrate (near) real-time monitoring in real-world deployments in the UK and overseas. Finally, you will work towards achieving impact with the project, e.g., by (co-)publishing reproducible technical documentation and a project report.
As a successful candidate, you will likely have interest in and experience with multiple (but not necessarily all) of the following aspects:
- Machine learning, AI,
- Embedded systems, microcontrollers, electronics, sensors, Internet of Things, wireless communication,
- A programming language,
- Scientific work, scientific/technical writing, and
- The natural environment.
If you are excited by this project but hesitate to apply, please do—we particularly encourage applications from candidates from underrepresented or non‑traditional paths. In your application, please include how your profile matches some/all of the five points listed above providing concrete examples or evidence. In addition, please confirm your expected availability during the project duration.
Please note that you will have to carry out some of the work in the Physical Sensing Lab in the Abacws building - this job cannot be completed entirely remotely.
The position my close before the advertised closing date if a suitable candidate is identified.