ENAC – Two PhD positions – Large-scale Habitat Suitability Mapping with Machine Learning

Your mission

As a PhD student, you will investigate the potential of deep learning models for describing the suitability of habitats to host animal and vegetal species. In particular, you will develop models based on remote sensing data to model habitats where species can be found and prosper. To do so, you will leverage large-scale database of species distributions such as iNaturalist, eBird or Pl@ntNet and work towards integrated solutions involving a large number of species. The methods to be developed will be informed by knowledge in ecology, for instance about species interactions and species location priors. Such models will then be used to establish migration and extinction scenarios due to climate change projections.

Technical challenges related to large-scale prediction, data non-stationarity and quality of crowdsourced labels will be at the core of the studies.

Main duties and responsibilities include

• Perform data acquisition of large amounts of satellite data.
• Create a database of species observation data from multiple crowdsourced sources.
• Develop deep learning-based methodologies to analyze the data and create species distribution maps at scale, including ecological prior knowledge.
• Build and test scenarios of habitat suitability related to climate change.
• Write publications.
• Attend international conferences.
• Participate to education of the ENAC faculty.

Your profile

• You have a Master in environmental engineering or computer science.
• You have experience with remote sensing, machine learning and computer vision.
• You are proficient in Python coding.
• You are fluent in English.
• You are motivated, curious and willing to work in a highly dynamic team.

We offer

• An opportunity to develop a scientific career in an exciting area of science.
• A unique opportunity to learn high-end techniques and approaches.
• Excellent educational conditions and competitive remuneration.
• A multi-cultural and stimulating scientific environment, in the new EPFL-Valais campus in Sion.

Start date                        May 1st, 2022

Work rate                        100%

Duration (if CDD)           1 year (candidacy examination) + up to 5 years after

How to apply:

Please send the following application documents in one single pdf-file :

Your application will only be considered if these documents are appended in one single pdf-file in the above stated order.

Please send your application documents to [email protected]