University of Nantes (UN) is a Higher education institution. Within the University, the team Remote Sensing and Benthic Ecology is recognized for its scientific expertise in coastal ecology. The team has developed a strong expertise in visible near infrared remote sensing applied to coastal areas, with a focus on intertidal zones dominated by sediment shores and colonized by benthic microalgae, macroalgae, and biogenic reefs (wild oysters, polychaetes). The team has been recently participating to an EU H2020 project on seagrass remote sensing (CoastObs, 2017 – 2021) and in a EU BiodivERsA project on microphytobenthos diversity and ecology (BIO-Tide, 2017 – 2020).
The postdoc will work on an international research project at the interface of remote sensing and marine ecology & biodiversity. The objective is to assess the potential of Earth Observation (EO) to study biodiversity in intertidal ecosystems, with a focus on sediment shores (beaches, estuaries, mudflats, and isolated rocky areas). The essential biodiversity variables (EBVs, sensu Muller-Karger, et al. 2018) of the main intertidal habitats (seagrass, microphytobenthos, macroalgae, oysters reef, and polychaetes reef) will be characterized in several study sites along the French Atlantic coast, in order to investigate the effects of climate change, human impacts, and natural drivers on the coastal zone.
Material and methods
The postdoc will analyse a hyperspectral reflectance library of intertidal primary producers and habitats, and will be in charge of building the spectral database, acquiring ad hoc field data in 2022, and compiling data available in the literature. The postdoc will investigate a variety of methods, from baseline radiometric indices to Machine Learning type classification to identify intertidal vegetation and main habitats from in situ and satellite data. In particular, the potential of on-going satellite missions, including Sentinel-2, VENuS, PRISMA and DESIS should be assessed. The postdoc will validate the algorithms over several pilot sites in Europe (France, Portugal, Germany), and use satellite time-series to study the influence of environmental drivers on intertidal EBVs.
Eligibility
A PhD degree in Environmental Sciences, Oceanography, Marine ecology, Remote Sensing, or a related field is required. Graduate students close to defending their dissertation and/or current postdocs looking for a new opportunity are both encouraged to apply.
Requirements
- A strong background in marine ecology and remote sensing is required.
- Experience using Earth Observation data.
- Proficiency with R, Python, or equivalent data processing software, and ability to produce well designed and documented code.
- Documented experience with writing manuscripts for peer-reviewed journal publications, and presenting work at international conferences.
Salary
Net monthly salary 2250 EUROS, including health insurance and social benefits.
The following skills would also be beneficial
- Experience in Deep Learning / Machine Learning applied to environmental sciences.
- Sufficient numerical ability to understand some fundamental theory behind deep learning algorithms. Strong statistical skills are particularly relevant.
- Experience in the ecology and biodiversity of benthic primary producers.
- Ability for field sampling in challenging environments such as intertidal mudflats.
- Experience in field radiometry.
- Experience in hyperspectral remote sensing.
- Experience in EU projects, including writing project deliverables & reporting.
How to apply
Send your CV, letter of motivation, and the name of two referees by email to Pierre Gernez and Laurent Barillé