Research Fellow in Computational Soundscape Ecology (Fixed Term
School of Life Sciences
Full time, fixed term (6 months)
Salary range: starting at £31,342 and rising to £37,394 per annum.
Closing date for applications: 18 May 2015
Expected start date: 1 October 2015
A 6 month full time Postdoctoral Research Fellow position is available from Oct 2015 in the Department of Evolution, Behaviour and Environment (EBE), within the lab of Dr Mika Peck, to investigate computational acoustic approaches to Rapid Biodiversity Assessment.
Efficient methods of biodiversity assessment are crucial in ecological research, conservation and land-management. Based on the premise that the structure of the soundscape of a habitat is a reliable indicator of biodiversity within it, community-level acoustic measures are emerging as a promising route. The aim of this project is to develop and validate acoustic indices (calculated from field recordings) as tools for biodiversity assessment. The successful applicant will bring technical expertise in signal processing and machine learning and work collaboratively in a small team.
The successful candidate will have a demonstrable track record of research in Music Information Retrieval, Computational Bioacoustics or strongly related areas. Experience in signal processing, statistics, machine listening and/or learning and strong programming skills are essential; an interest in bioacoustics, ecology and/ or evolutionary theory would be a distinct advantage. Applicants should possess a completed doctorate in a relevant field or have equivalent professional experience, including working in collaborative research teams.
Good communication skills, a passion for innovation, and an ability to work productively as part of a trans-disciplinary team are essential for this position.
The EBE is an enthusiastic and dynamic group of researchers, working at the cutting edge of issues of fundamental importance to life on earth. You will work with a small interdisciplinary team interested in the application of technology in conservation.
Efficient methods of biodiversity assessment are crucial in ecological research, conservation and land-management. Based on the premise that the structure of the soundscape of a habitat is a reliable indicator of biodiversity within it, community-level acoustic measures are emerging as a promising route. The aim of this project is to develop and validate acoustic indices (calculated from field recordings) as tools for biodiversity assessment. The successful applicant will bring technical expertise in signal processing and machine learning and work collaboratively in a small team.
The successful candidate will have a demonstrable track record of research in Music Information Retrieval, Computational Bioacoustics or strongly related areas. Experience in signal processing, statistics, machine listening and/or learning and strong programming skills are essential; an interest in bioacoustics, ecology and/ or evolutionary theory would be a distinct advantage. Applicants should possess a completed doctorate in a relevant field or have equivalent professional experience, including working in collaborative research teams.
Good communication skills, a passion for innovation, and an ability to work productively as part of a trans-disciplinary team are essential for this position.
The EBE is an enthusiastic and dynamic group of researchers, working at the cutting edge of issues of fundamental importance to life on earth. You will work with a small interdisciplinary team interested in the application of technology in conservation.
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