Ecosystem Modelling Specialist

2 days ago

Davangere, Karnataka, India beBeeEnvironmental Full time ₹ 1,50,00,000 - ₹ 2,00,00,000
Modelling and Development Expert

We are seeking an experienced environmental modeller with advanced programming skills to develop, implement, and maintain components of the Agricarbon Ecosystem Model (AEM) using Python.

About the Role:

The successful candidate will be responsible for implementing and 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.

You will contribute to the development and maintenance of the Bayesian data assimilation framework that underpins the AEM, ensuring robust uncertainty quantification and model calibration.

Your technical expertise will also include configuring, running, and extending existing model components, such as LINTUL-5, LINGRA, RothPC-N, developing Python implementations that maximise the benefit of our access to the world’s largest soil carbon database.

Key Responsibilities:
  1. Developing and integrating model components, including plant growth, soil carbon, water, nitrogen, and livestock models.
  2. Contributing to the development and maintenance of the Bayesian data assimilation framework.
  3. Configuring, running, and extending existing model components.
  4. Evaluating and implementing machine learning and statistical models to enhance overall accuracy and predictive power.
  5. Maintaining high standards of code quality, reliability, performance, and maintainability.
Requirements:
  • Advanced programming skills in Python, with experience in scientific libraries (NumPy, SciPy, Pandas, scikit-learn, GeoPandas) and Bayesian statistical libraries (PyMC or similar).
  • Proven 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.
  • Code quality focus, with experience in software development best practices, version control (Git), testing frameworks, and code documentation.
Preferred Qualifications:
  • Experience with Bayesian methods and data assimilation frameworks.
  • Familiarity with soil carbon and crop growth models, grassland models, integrated agricultural system models.
  • Knowledge of nitrogen cycling and soil-plant-atmosphere interactions.
  • Familiarity with data assimilation using satellite-derived data.
  • Experience with cloud computing platforms for large-scale data processing.
What We Offer:

A challenging and rewarding role with opportunities for professional growth and development.

A collaborative and supportive work environment.

The opportunity to contribute to cutting-edge research and projects.

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