Environmental Systems Modeller

2 days ago

Hubli, Karnataka, India beBeeEcosystemModelling Full time US$ 1,00,000 - US$ 1,20,000
Ecosystem Modeller for Agricultural Systems

We are seeking a highly skilled Ecosystem Modeller to join our team. The successful candidate will have extensive experience in developing and implementing environmental models, particularly in the agricultural sector.

Job Description

The role involves developing and maintaining components of the Agricarbon Ecosystem Model (AEM) using Python. This includes working with agricultural ecosystem models, such as plant growth models, soil organic carbon models, and grazing models.

  • Developing and implementing model components, including plant growth models, soil organic carbon models, and grazing models.
  • Maintaining the integration between different AEM components, ensuring seamless data flow between plant growth, soil carbon, water, nitrogen, and livestock models within the Bayesian data assimilation framework.
  • Contributing to the development and maintenance of the Bayesian data assimilation framework that underpins the AEM, ensuring robust uncertainty quantification and model calibration.
  • Configuring, running, and extending existing model components, such as LINTUL-5 (arable crops), LINGRA (grass), RothPC-N (soil organic carbon and nitrogen).
  • Developing Python implementations that maximise the benefit of our access to the world's largest soil carbon database.
  • Evaluating and implementing machine learning and statistical models using Python libraries to enhance overall accuracy and predictive power.
  • Ensuring all modelling code meets high standards for reliability, performance, and maintainability, with comprehensive testing and documentation.
  • Working closely with our Principal Soil Modeller to translate scientific requirements into robust technical solutions.
Required Skills and Qualifications

To be successful in this role, you will need:

  • Advanced programming skills in Python, including proficiency with scientific libraries (NumPy, SciPy, Pandas, scikit-learn, GeoPandas) and Bayesian statistical libraries (PyMC or similar).
  • Extensive experience developing and working with ecosystem models or related areas.
  • Data science proficiency, including experience with machine learning techniques and their application to environmental data, including model validation and statistical analysis.
  • Code quality focus, including experience with software development best practices, version control (Git), testing frameworks, and code documentation.
  • Excellent analytical and problem-solving abilities, with extreme attention to detail and a rigorous approach to model development.
Benefits

This is an exciting opportunity to work on complex modelling challenges and contribute to the development of cutting-edge environmental models.

Others

You will be part of a multi-disciplinary team reflecting engineering, GIS, soil science, quality management, and data systems, and the commercial team, as well as collaborating effectively with external partners.

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