Open Position as Director of Applied Biodiversity Science (80-100%, Zurich, fixed-term)

We are offering a position in biodiversity theory, remote sensing and geospatial data science at Crowther Lab, ETH Zurich – a unique research group specializing in global ecosystem ecology. We aim to form the bridge between theoretical ecology and direct practical action by generating a global assessment of terrestrial biodiversity change over time.

Project background

The focus of this position is to direct science related to the implementation of biodiversity assessments at high spatiotemporal resolution, incorporating the complexity of biodiversity across genetic, species, and ecosystem levels. The Crowther Lab has developed various approaches to model ecosystem information and processes across the globe using large ecological datasets. We now aim to develop more tailored maps relevant to the needs of a variety of stakeholders who need to a) better understand the biodiversity in their ecosystem, b) support the development of conservation and restoration strategies and c) monitor change over time.

Job description

We are looking for a geospatial scientist excited to lead the technical side of developing novel biodiversity indicator metrics, computational infrastructure and monitoring approaches to provide insights about terrestrial ecosystem health and intactness. The candidate will leverage and improve the existing modelling pipelines to develop local and global ecological spatial products by making use of ground-truthed data from external partner organizations and remotely sensed imagery. Candidates should have the theoretical background in ecology or ecological or complex systems dynamics, and the practical skills to manage, integrate and interpret large ecological datasets. The ultimate goal would be to work with economists and finance specialists to integrate this biodiversity assessments methodology into emerging finance systems.

Your profile

We look for a highly motivated candidate with a background in ecological or complex systems theory, and experience with geospatial and remote sensing analyses. The ideal candidate has a PhD and/or applied experience working with geospatial models, and strong skills in data science and machine learning. Direct experience monitoring and quantifying ecosystem structure and/or function is highly preferable. Knowledge of multiple programming languages is required, in particular R and Python; additional languages and familiarity with Google Earth Engine and/or GIS software is useful but not essential. Experience with ensemble machine learning, neural networks, and/or random forests is preferable. 


The position is for 2 years (with a 12 month performance review), but will be undertaken with the potential opportunity of making the position permanent as we seek to expand their team of scientists, programmers and enhance their impact across the global conservation community.

To apply, please submit a CV and a one-page statement explaining why you are interested in this position through the online application portal of ETH Zurich by 19 August 2022. Late applications or applications submitted by email or post will not be considered.

For further information about the application or group, please contact Group Manager, Emily Clark at

ETH Zurich is an equal opportunity and family friendly employer. All candidates will be evaluated based on their merits and qualifications, without regard to gender, sexual orientation, race, age, religion, disability etc. Candidates from underrepresented and traditionally disadvantaged backgrounds are particularly encouraged to apply.