The Department of Environmental Sciences (EVSC) and the School of Architecture (SOA) at the University of Virginia invite applicants for an Assistant Professor in landscape science. We seek applicants whose research and teaching advance knowledge of environmental systems and address problems of societal relevance. The ideal candidate is an empirically oriented environmental scientist whose work addresses problems of regions, landscapes, or land-use patterns. This position is open to all areas of environmental sciences and will prioritize research and teaching in the ecologic, hydrologic, geologic, or atmospheric domains.
Job Purpose As our Senior Scientist – Vegetation-Climate Interactions , the key duties are: Drive forward the work for science projects on vegetation-climate interactions. Collate and analyse Earth system data… More
We are seeking a highly motivated young scientist with profound experience on greenhouse gas (GHG) flux measurements from terrestrial ecosystems by using eddy covariance (EC) techniques. The successful candidate will… More
The position is for three years starting May 1, 2021 and is funded by the German Science Foundation (DFG) and within the French-German NO-PIMS project (What is the role of exogenous NO for plants, microbes, and their interactions in soil?) as jointly funded by DFG and the French ANR (Agence nationale de la recherche).
Analysis of ecosystem-atmosphere flux data for evidencing putative impacts of changes in light regime and pollutants deposition during the COVID 19 lockdown.
Vacancy: 2 PhD positions in data assimilation / inverse modelling of the carbon cycle at Lund University, Sweden The Carbon Cycle Data Assimilation group at the Department of Physical Geography… More
The PhD project will help to get a more complete picture of the consequences of
extreme events on the behavior of different ecosystems. For this purpose, the PhD
shall evaluate existing data sets of biotic and abiotic variables including flux data,
with their influence on carbon and water fluxes by linking the ecohydrological,
(micro-) climatological, geophysical, hydrogeological, and pedological information on
plot and ecosystem scale.
Main tasks will be the development of innovative strategies to analyse existing field
well as (geo)statistical methods including machine learning approaches.
Applicants with a degree in atmospheric science, physics, environmental or
geosciences or a related field and a background in micrometeorology and
data-assimilation procedures are encouraged to apply. The candidate should
demonstrate programming skills (e.g., Python or Fortran), experience with scientific
is advantageous. Communication skills in English and willingness to work in a team,
present and publish results at scientific conferences and peer-reviewed scientific
journals are required.
We seek a doctoral student to work with carbon upscaling and remote sensing.