WILDLABS
World Wide Fund for Nature/ World Wildlife Fund (WWF)
See the original posting here.
About Naturalis
Naturalis Biodiversity Center in Leiden is the Dutch national research institute for biodiversity and systematics. With our collection of 42 million specimens, one of the world's largest natural history collections, and our state-of-the-art research facilities we offer the (inter)national research infrastructure for species identification and monitoring (for example in the ARISE and DiSSCo projects). We run nature identification services processing many millions of images/month for users including citizens and regional government agencies. We closely collaborate with many Dutch universities, research institutes, industry, and government. We host over 120 researchers including 15 academia embedded professors and 40 PhD students. We present the history of our planet, and the diversity of life on Earth, through permanent and temporary museum exhibitions, educational programmes, and online presence, with more than 400,000 visitors per year. All in all, a unique combination of science and culture in the Netherlands and elsewhere in the world!
The research department is organised in 9 research groups comprising researchers and their postdocs and PhD-students. Naturalis has a completely new lab building, including state-of-the-art molecular facilities, microCT scanners and electron microscopy (SEM and TEM). Naturalis is looking for a Postdoctoral fellow in AI for Ultrasonic Bioacoustic Monitoring.
The position
Would you like to curate datasets and train AI to detect and classify bats, insects and other ultrasonic animals beyond the range of human hearing? To help monitor biodiversity across Europe? To collaborate with AI and biodiversity experts, as part of a team and with partners in many European countries?
Naturalis is looking for a Postdoctoral Fellow in AI for Ultrasonic Bioacoustic Monitoring. The postdoc will be based in the Evolutionary Ecology group. We have an 18-month position available, funded by the MAMBO project and also collaborating with other closely-related projects in the team (GUARDEN, Bioacoustic AI). At Naturalis, you will work in a team with experts in both AI and biodiversity, and you will also collaborate with project partners in other European institutions.
Our team has developed and deployed AI algorithms for recognising the sounds and images of Europe’s wildlife. In this project you will extend this work to the ultrasonic sounds of bats, insects and other animals. This involves curating open datasets of sound, as well as training deep learning, and validating that these methods will perform reliable recognition in the wild.
Tasks:
- Obtain training data for bats and other animals, from existing sources, including working with others to facilitate open publication of datasets.
- Train and evaluate AI models for ultrasonic animal sounds, including bats and insects.
- Investigate advanced AI methods for the above purpose.
- Work with colleagues to deploy AI models as services.
- Write and submit high-quality academic work for publication.
- Provide input to the planning of large-scale nature AI developments.
General requirements
and skills
Essential knowledge, skills and experience:
- A PhD* in a topic such as animal acoustics, machine learning, quantitative ecology, quantitative biology, signal processing or similar.
- Evidence of the ability to conduct high-quality research and write publications for high impact scientific journals/proceedings.
- Proficient in programming e.g. Python, PyTorch, or Tensorflow.
Excellent knowledge of the English language (written and verbal) is required, as well as a scientific and critical attitude, outstanding time management and organisational skills, and the ability to work independently as well as collaboratively within the project and the Naturalis research group. Additionally, you have good communication skills and are eager to contribute to knowledge dissemination and outreach activities.
Desirable knowledge, skills and experience:
- Experience of working with audio data, ideally ultrasound and/or automatic sound recognition.
- Experience collaborating with colleagues in other research disciplines.
- An interest in/affinity with biodiversity, and the field of natural sciences and biology.
- Experience in grant writing/demonstrated ability to acquire external funding.
- Work experience in multiple research environments.
* We will consider your application if you have not yet obtained your PhD diploma, provided that it can be confirmed by the university (before the start date) that you will receive your degree and that your defense is scheduled.
Offerings
A contract (36 hours per week) for a period of one year, to be extended with six months after a successful first year evaluation, and a monthly starting salary between € 3,641 and € 4,731 gross, depending on relevant experience. Additionally, you will receive an allowance for travel expenses, holiday allowance (8%) and year-end bonus (3.4%). The planned start date is June 1st 2025. The successful candidate will be employed by Naturalis, and will benefit from our inspiring working atmosphere, as well as the buzzing scientific atmosphere of Leiden. Our Research Coordination Office also provides ample support to our scientific staff. Our institute promotes gender equality and wants to enhance the diversity of staff members.
The procedure
To apply, please submit a single PDF document including:
- A motivation letter
- A CV (including a list of publications)
- The names and contact details of two referees.
Please submit your application by April 6 using the application form.
Feel free to contact both Dr. Dan Stowell (Associate Professor in AI & Biodiversity; dan.stowell@naturalis.nl; http://mcld.co.uk/research/ ) and Dr. Vincent Kalkman (Researcher; vincent.kalkman@naturalis.nl; https://www.naturalis.nl/en/vincent-kalkman) with questions about the position. For questions about the procedure, please contact HR (sollicitaties@naturalis.nl).
Naturalis endorses the Cultural Diversity Code. In the case of equal suitability, preference is given to the candidate who reinforces diversity within the team.