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Vacancies 24 Feb.

Postdoctoral Scholar in Ecosystem Ecology Modeling, Michigan Technological University, US

Michigan Technological University and the Tropical Responses to Altered Climate Experiment (TRACE; https://www.forestwarming.org) is seeking a full-time modeling ecosystem ecologist postdoctoral researcher. The position will involve the development and evaluation of ELM-FATES (the land component of the DOE Earth system model E3SM coupled with the Functionally Assembled Terrestrial Ecosystem Simulator - FATES) using data from the TRACE site. TRACE is an in-situ forest warming experiment taking place in the Luquillo Experimental Forest in eastern Puerto Rico. Duties include synthesis and analysis of observational and experimental data, model-data integration, execution and analysis of model simulations to understand tropical ecosystem responses to changing environments, and publication in leading journals. This is a two-year, full-time position based in Houghton, Michigan within the College of Forest Resources and Environmental Science at Michigan Tech, within the lab of Dr. Molly Cavaleri. For more about life in Houghton, see: https://www.mtu.edu/about/#area). Collaboration with TRACE principal investigators and Oak Ridge National Laboratory will be essential to the success of this position. Please see the full job ad and application instructions here: https://www.employment.mtu.edu/cw/en-us/job/492793. Screening of applicants will begin February 10, 2022 and continue until the position is filled. We are aiming for a May 2022 start date, but this is negotiable.

 

Postdoc, Wageningen University & Research

As postdoc you will focus on ‘The Spatial Limitations of Knowledge’ project that aims to advance spatial hydrology using ‘Big Data’ approaches. Globally applied models rely on process descriptions that are not equally valid in all climates or environments. This is especially true for soil parameterizations, which are often based on pedo-transfer functions developed in very specific settings. Your challenge will be to take existing simulations from global land surface and hydrological models and confront them with ground and remote sensing observations using advanced data analysis techniques. You will critically reflect on the influence of model choices and practices on the results to propose a way forward for global modelling. You will be able to draw on expertise on soil physics, hydrological and land surface modelling, remote sensing and machine learning within HWM and elsewhere in WUR, as well as our strong network of national and international collaborators. Deadline: N/A. See link for detail info https://www.wur.nl/en/vacancy/Postdoc-Evaluating-Soil-Hydrological-Modelling-at-the-Global-Scale-using-Big-Data-.htm 


Junior Research Scientist, INRA, France

You will join the SOLS Research Unit in Orléans (France), whose research focuses on the physical and geochemical functioning of soils. To implement your research program, you will work closely with all the scientists at the site in Orléans (SOLS Research Unit and INFOSOL Service Unit) working on soils and with skills in pedology, spatialization, modelling, data processing, especially in the field of spatial data and their temporal dynamics, and database management. For your modelling work, it will be possible to draw on the INRAE Virtual Soil modelling platform (https://www6.inrae.fr/vsoil/The-project). Deadline for submission: March 8, see link for detail info

https://jobs.inrae.fr/en/open-competitions/open-competitions-research-scientists-job-profiles-crcn/cr-2022-agroecosys-4  

 

Postdoc, Humboldt Foundation, Germany

The Humboldt Foundation is scouting for researchers (postdocs) from underrepresented regions of the globe. For that, they developed a scouting program particularly dedicated to supporting excellent female scientists, and I have the honor to serve as one of their scouts. In this context, I am looking for a scientist with expertise in ecology/ macroecology. For this second round of candidates (2022), there are three main topics: 

1) The candidate should be interested in synthesizing/modelling global data on soil biodiversity, carbon cycling, and soil-biosphere-atmosphere interaction

2) The candidate should be interested in plant-mycorrhizae interactions and work in the broad context of the MyDiv Experiment 

3) The candidate should be interested in biodiversity effects on ecosystem functioning with a focus on plant-soil interactions in the broad context of the Jena Experiment on mechanisms underlying long-term biodiversity effects on ecosystem functioning 

More information about the funding program can be found here: https://www.humboldt-foundation.de/en/apply/sponsorshipprogrammes/henriette-herz-scouting-programme

In case of interest, the candidates should send (1) a motivation letter, (2) a one-pager on a potential research topic, and (3) their CV (combined in one PDF) to Svenja Haenzel (svenja.haenzel@idiv.de) by February 28, 2022. Potential questions should also be sent to Svenja Haenzel.

 

 PostDoc Researcher in the field of plant modelling at Jülich, Germany
 
100% (E13 TVöD) | fixed-term, initially until December 31st, 2025, with the possibility of an extension
 
In project C02, we are looking for a Postdoc researcher in the field of plant modelling, with a background in plant physiology, drought stress and, ideally, experience in functional structural plant modelling and/or continental scale modeling (CLM5).
 
 
 
PhD Position - Terrestrial Modeling and Data Analytics PhD Position, Jülich, Germany

At the Institute of Bio- and Geosciences – Agrosphere (IBG-3) we conduct research to improve our understanding of biogeochemical and hydrological processes in terrestrial systems. Specific studies focus on environmental controls on biogeochemical cycling of elements, the analysis of exchange processes and nutrient dynamics in the soil-plant-atmosphere continuum. A combination of experiments, modelling and innovative observation technologies is used to bridge the gap between model, process and management scale. Our research contributes to the sustainable and resource-conserving use of soils and water and to the quantification of the effect of climate and land use change on terrestrial ecosystems. We offer a competent and interdisciplinary working environment, as well as an excellent framework in the areas of experiments and modelling.

Your Job:

  • Develop and apply coupled terrestrial models in the research areas hydrogeology (groundwater), hydrology (soil and land surface including vegetation), and meteorology (weather/climate)
  • Perform scientific simulations in supercomputer environments
  • Analyze large geoscientific data sets
  • Present and publish results at international conference and peer reviewer journals
 
Further positions:
 
PhD position: Scientific Discovery in Earth System Science: Applying Deep Learning Technologies in the Exploration of Big Data from Terrestrial Modeling
 
You will mine and explore big data from Terrestrial Modeling of the coupled water, energy, and nutrient cycle from groundwater to the top of the atmosphere. These type of simulations result in very large data sets (O(1000) TB) with hundreds of output variables that are correlated over short and long distances and timer periods via complex non-linear processes. Identification and characterization of these correlations and previously unidentified interacting mechanism constitutes a grand challenge in the Earth Science; only a fraction of available information from these simulations can be used today to predict, for example, extreme events such as drought and floods. In this project we tackle this challenge by developing and applying state of the art machine and deep learning technologies in massively parallel supercomputer environments leading to novel data mining and exploration capacities and new discoveries of previously unknown information in big simulation data. The project will be conducted in collaboration with the German Aerospace Center (DLR), and the Centre of High-Performance Computing in Terrestrial System, Geoverbund ABC/J.
 
Further positions:
 
 

 

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