Postdoctoral Research Assistant in Applied Machine Learning for Acoustic Data Analysis


Grade 7: £32,817 - £40,322 p.a.

Closing date

Oct 21, 2020 12:00PM


We are seeking a full-time Postdoctoral Research Assistant in applied machine learning for acoustic data analysis. The successful applicant will join the Machine Learning Research Group at the Department of Engineering Science (central Oxford). The post is part of the HumBug project (, which aims to develop next-generation mosquito detectors to aid our understanding of malarial transmission. The post is fixed-term for up to 6 months.

You will be responsible for research into acoustic time-series modelling techniques, with a particular focus on detection algorithms for mosquitoes. You will also be involved in system integration, verification and validation, as well as collation and curation of databases.  The role will focus as much on creating robust, reliable solutions as it will on innovation, suiting a candidate who is motivated by seeing end to end solutions in place to address real-world applications.

You should have a relevant PhD/DPhil (or have submitted your thesis and await completion), as well as possess a good first degree in Engineering, Physics, Computer Science, Mathematics, Statistics or similar. You should have specialisation in machine learning models for acoustic data analysis. Experience in practical applications of detection algorithms in uncertain domains is essential, as well as expertise and experience in computer programming. Experience of acoustic data analysis for insect identification is particularly beneficial. You should have a track record of published work concomitant with relevant experience and the ability to work well both independently and as part of a team.

Informal enquiries may be addressed to Prof Stephen Roberts (

Further information about working at the Department, please see

Only applications received before midday on Wednesday, 21 October 2020 can be considered. You will be required to upload a covering letter/supporting statement, including a brief statement of research interests (describing how past experience and future plans fit with the advertised position), CV and the details of two referees as part of your online application.

The Department holds an Athena Swan Bronze award, highlighting its commitment to promoting women in Science, Engineering and Technology. For more information about working at the Department, see

Contact name

Prof Stephen Roberts

Contact email