Job Description
We are currently seeking a Research Engineer to support machine learning research in air quality, atmospheric science, and environmental data analytics. The successful candidate will develop and evaluate predictive models using air quality, meteorological, and sensor datasets. Responsibilities include data compilation and preprocessing, model validation, scientific visualization, and contributing to publications, reports, and research projects. Candidates should be comfortable working independently while engaging with multidisciplinary teams. This role is ideal for someone who enjoys translating complex environmental data into practical insights and robust computational solutions.
Qualifications
- Bachelor's or Masters' degree in statistics, data science, atmospheric science, environmental science/engineering, or a related discipline
- Good Python programming skills, with good knowledge in Pandas, NumPy, SciPy, Scikit-Learn, Matplotlib or related tools
- Basic understanding of model evaluation, cross-validation, hyperparameter optimization, uncertainty analysis, and interpretable machine learning is required
- Experience in projects using supervised and unsupervised machine learning methods, such as regression, classification, clustering etc. (especially in atmospheric applications) is an added advantage
- Experience processing meteorological, air quality, or environmental sensor data is a bonus
- Strong scientific communication, documentation, and technical writing skills
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