Radar Intern

Position: Summer Research Intern: Weather & Machine Learning Duration: 10–12 weeks Level: Undergraduate or Graduate Overview: We are seeking a motivated student with coursework in meteorology and hands-on experience with machine learning to join our research team for the summer. The intern will contribute to a project focused on using machine learning to better understand and track microscale features within winter weather systems using radar data. Responsibilities Work with radar datasets to identify and organize cases of microscale features Assist in preparing and processing data for use in machine learning models Help evaluate and visualize model results using Python-based tools Contribute to team meetings and discussions about storm behavior and model performance Document progress and assist in preparing summaries of findings Qualifications Currently enrolled in an undergraduate or graduate program in meteorology, atmospheric science, or a related field Basic familiarity with radar products through coursework or experience Prior coursework or project experience in machine learning or data science Proficiency in Python for data analysis Preferred Coursework or experience in radar meteorology Experience with or understanding of cloud seeding atmospheric effects Familiarity with deep learning frameworks such as PyTorch or TensorFlow Experience with data analysis tools such as Py-ART, MetPy, xarray, or similar Prior research experience of any kind (REU, class projects, lab work) What You Will Gain Hands-on experience applying machine learning to real operational radar data Mentorship from researchers across meteorology and data science A meaningful research contribution suitable for graduate school applications Collaborative work environment bridging atmospheric science and modern data science methods

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