Senior Ecosystem Modeller

2 days ago

Lucknow, Uttar Pradesh, India beBeeSoftwareEngineer Full time ₹ 22,00,000 - ₹ 27,00,000

Job Opportunity:

We are seeking an experienced Environmental Modeller to join our team and contribute to the development of the Agricarbon Ecosystem Model (AEM).

Required Skills and Qualifications
  • Advanced Programming Skills: Extensive experience in Python programming for data science and environmental modelling, including proficiency with scientific libraries such as NumPy, SciPy, Pandas, scikit-learn, and GeoPandas.
  • Environmental Modelling Experience: Proven experience developing and working with ecosystem models or related areas.
  • Data Science Proficiency: Extensive experience with machine learning techniques and their application to environmental data, including model validation and statistical analysis.
  • Code Quality Focus: Experience with software development best practices including version control (Git), testing frameworks, and code documentation.
  • Educational Background: Master's degree or PhD in Data Science, Environmental Science, Computer Science, or related field with a strong focus on modelling and programming.


Key Responsibilities
  • Model Components & Integration: Working with agricultural ecosystem models (AEM) including plant growth models (LINTUL-5, LINGRA), soil organic carbon models (RothPC, RothPC-N), soil water models, mineral nitrogen models, and grazing models.
  • Model Integration: 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.
  • Technical Development: Contributing to the development and maintenance of the Bayesian data assimilation framework that underpins the AEM, ensuring robust uncertainty quantification and model calibration.
  • Machine Learning Integration: Evaluating and implementing machine learning and statistical models using Python libraries to enhance overall accuracy and predictive power, potentially as part of ensemble modelling approaches.


Benefits
  • Technical Collaboration: Working closely with our Principal Soil Modeller to translate scientific requirements into robust technical solutions, providing programming expertise to support complex modelling challenges.
  • Data & Validation: Designing and implementing automated testing frameworks to validate and improve model performance, ensuring statistical rigour in all implementations.
  • Communication & Documentation: Producing comprehensive technical documentation, code comments, and user guides for all modelling implementations.

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