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From October 2024 to March 2025, I undertook a six-month paid internship at AEE - Institute for Sustainable Technologies in Graz, Austria, focusing on the development of a national heat map layer for water sources. This work involved data processing, geostatistical analyses, and visualization of results to support renewable energy projects.
During my internship, I gained extensive experience in geostatistics and environmental data analysis. I learned to handle large datasets, apply different interpolation methods (e.g., Top Kriging and exponential regression), and critically compare them. The practical application of Geographic Information Systems (GIS) and statistical modeling techniques was particularly valuable.
The working environment was professional and supportive. I had the opportunity to collaborate closely with experts from various fields, which significantly enhanced my learning experience. The highlights of the internship included working on a real-world environmental problem directly relevant to energy transition and creating insightful maps for result visualization. One challenge was the considerable amount of time required for data preparation and cleaning.
I found this internship through IAESTE and applied directly to HR of the company. Alternatively, a speculative application can be beneficial, especially for those with experience in renewable energy.
Key prerequisites for the internship include basic knowledge of geostatistics, GIS, and data analysis. An academic background in environmental sciences, geoinformatics, or related fields is beneficial.
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