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3 days ago
Develop and implement ecosystem models to simulate environmental systems. Key Responsibilities:
- Work with plant growth models such as LINTUL-5 and soil carbon models including RothPC-N.
- Implement integration between different model components ensuring seamless data flow within the Bayesian framework.
- Technical Development:
- Contribute to the development and maintenance of the Bayesian data assimilation framework for robust uncertainty quantification and model calibration.
- Configure, run and extend existing model components such as LINTUL-5 (arable crops) and RothPC-N (soil organic carbon and nitrogen).
- Evaluate and implement machine learning and statistical models to enhance overall accuracy and predictive power.
- You must have advanced programming skills in Python programming for data science and environmental modelling.
- Must have experience developing and working with ecosystem models or related areas.
- Must have extensive experience with machine learning techniques and their application to environmental data.
- Must have experience with software development best practices.
- Must have excellent analytical and problem-solving abilities.
- Educational background: Master's degree or PhD in Data Science, Environmental Science, Computer Science, or related field.
- Experience with Bayesian methods and data assimilation frameworks.
- Familiarity with crop growth models such as LINTUL and soil-plant-atmosphere interactions.
- Geospatial data handling experience.
- Familiarity with cloud computing platforms.
Environmental Modeller Data Scientist Ecosystem Model Bayesian Framework Python
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