Earth System Data Science and Remote Sensing (MSc)
A specialized Master's programme combining Earth system science, remote sensing, and data science.
Best for:Best for students with a background in geosciences or data science seeking to specialize in Earth observation and environmental analytics.
Overview
The Master of Science in Earth System Data Science and Remote Sensing at Leipzig University is designed to train the next generation of scientists to address global environmental challenges. The curriculum integrates domain knowledge in Earth and environmental sciences with advanced quantitative methods, coding, and state-of-the-art remote sensing technology. Students gain expertise in analyzing global data streams to develop solutions for climate change, biodiversity loss, and land transformation. The programme emphasizes a balance between methodological rigor and practical application through specialized modules and a mandatory research internship.
What you'll do
- Complete 120 ECTS credits over four semesters including core modules and a Master's thesis.
- Develop proficiency in multi- and hyperspectral remote sensing, radar, and Lidar technologies.
- Apply machine learning and artificial intelligence techniques to spatio-temporal Earth system data.
- Undertake a six-week research internship at a national or international institution.
- Engage in specialized application fields such as meteorology, geoecology, or biodiversity research.
- Participate in soft skills training including scientific writing and research data management.
Requirements
Degree required: BSc in a geoscience, environmental science, or data science related programme.
Degree offered: Master of Science
Language: English B2 level; official certificate required (e.g., IELTS 5.5, TOEFL iBT 72).
Instruction: English
- Minimum 35 ECTS in geography, Earth system sciences, environmental sciences, life science, data science, remote sensing, or GIS.
- Basic knowledge in statistics (minimum 5 ECTS).
- Basic skills in a scripting or programming language for scientific computing (e.g., Python, R, Julia).
- English language proficiency at B2 level.
- Hold a first professionally recognized university degree.
- Meet subject-specific ECTS requirements in relevant scientific fields.
Funding & terms
Programme and admissions
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How to apply
Deadline: 2027-05-31
Applications must be submitted via the uni-assist portal. Applicants should provide a CV, a letter of motivation, a transcript of records, and proof of relevant experience.
- CV
- Letter of motivation
- Transcript of records
- Proof of relevant vocational training or internships
Contact
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