
Environmental Model Developer
23 hours ago
**Environmental Modelling Software Engineer Position Available**
- We are seeking a highly skilled environmental modelling software engineer to join our growing team.
As an experienced environmental modeller with strong programming expertise, you will be responsible for developing, implementing, and maintaining 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.
You 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, as well as collaborating effectively with external partners.
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
**Required Skills and Qualifications:**
- Advanced Programming Skills: Extensive experience in Python programming for data science and environmental modelling, including proficiency with scientific libraries (NumPy, SciPy, Pandas, scikit-learn, GeoPandas) and Bayesian statistical libraries (PyMC or similar)
- 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
**Benefits:
- A dynamic and collaborative work environment
- Ongoing professional development opportunities
- Competitive salary and benefits package
**Others:
- 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
- Nice to have: Experience with Bayesian methods and data assimilation frameworks, familiarity with Soil carbon and crop growth models, knowledge of nitrogen cycling and soil-plant-atmosphere interactions, geospatial data handling experience, etc.
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