Modelling Environmental Systems Specialist

1 day ago

Nagpur, Maharashtra, India beBeeEcosystem Full time ₹ 2,00,00,000 - ₹ 2,50,00,000

Job Title:

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Ecosystem Modelling Software Engineer

This is a unique opportunity for an experienced environmental modeller with strong programming expertise to work on the development, implementation, and maintenance of components of the Agricarbon Ecosystem Model (AEM) using Python.

Your advanced programming skills will be crucial in translating complex modelling concepts into robust, production-ready code that enhances our ability to make accurate predictions of soil carbon levels and agricultural system interactions.

The successful candidate will need to be adaptable - capable of working independently and as a key member of a multi-disciplinary team reflecting engineering, GIS, soil science, quality management, and data systems.

Main Responsibilities:

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  1. Model Components & Integration: Working with agricultural ecosystem models including plant growth models such as LINTUL-5 and soil organic carbon models like RothPC.

  2. 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.

  3. Bayesian Framework Development: Contributing to the development and maintenance of the Bayesian data assimilation framework that underpins the AEM.

  4. Model Development: Configuring, running, and extending existing model components such as LINTUL-5 and developing Python implementations that maximise the benefit of our access to the world's largest soil carbon database.

  5. Machine Learning Integration: Evaluating and implementing machine learning and statistical models using Python libraries to enhance overall accuracy and predictive power.

Requirements:

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  • Advanced Programming Skills: Extensive experience in Python programming for data science and environmental modelling, including proficiency with scientific libraries such as NumPy and Bayesian statistical libraries like PyMC.

  • 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 and testing frameworks.

Benefits:

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  • Opportunity to work on cutting-edge environmental modelling projects.

  • Collaborative and dynamic work environment.

  • Professional development opportunities.

Others:

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  • A comprehensive benefits package.

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