Du wendest maschinelles Lernen auf geospatiale Vorhersagen an, berechnest städtische Metriken und entwickelst neue Embedding-Modelle.
Anforderungen
- •Currently enrolled in a master's program
- •Preferred study subjects: Data Science, Computer Science, GIS
- •Good understanding of Python and libraries
- •Familiarity with Pytorch framework
- •Basic understanding of machine learning concepts
- •Experience with git
- •Understanding of GIS is a plus
- •Confident in English
- •Strong organizational skills
- •Strong communication skills
- •Proficiency in Microsoft Office Suite
Deine Aufgaben
- •Geospatial-Maschinenlernmodell auf Vorhersageaufgaben anwenden
- •Städtische Morphologiemetriken mit offenen geografischen Daten berechnen
- •Neues geospatiales Embedding-Modell entwickeln
Deine Vorteile
Innovative Projekte
Globale Zusammenarbeit
Umfangreiche Netzwerke
Original Beschreibung
Internship (m/f/d) - Geospatial Embeddings at EIfER Europäisches Institut für Energieforschung EDF-KIT EWIV | softgarden
Become part of EIFER and drive climate solutions where science meets industry.
EIFER seeks a student for an internship position (m/f/d) in the field of "Geospatial Embeddings".
Start: 01.07.2025
Duration: max. 6 months (compulsory internship)
Weekly working hours: 39.5
Remuneration: 560€ monthly
In this internship, you will apply machine learning methods in a geospatial context to capture and represent the distinct character of places. You assess its effectiveness in acting as a predictor of missing data, as well as develop and evaluate a more advanced embedding model in the context of an existing open-source library.
Relevant papers (recommended to read in order):
1. SRAI: Towards Standardization of Geospatial AI
2. Hex2vec – Context-Aware Embedding H3 Hexagons with OpenStreetMap Tags
3. GeoVex: Geospatial Vectors with Hexagonal Convolutional Autoencoders
* Applying geospatial machine learning model to prediction tasks
* Calculating urban morphology metrics using open geographic data
* Developing a new geospatial embedding model
* Currently enrolled as a University student in a master program
preferred study subjects: Data Science, Computer Science, Geographic Information Systems.
* Good understanding of Python and its data science libraries (especially pandas)
* Familiarity with the Pytorch framework
* Basic understanding of machine learning concepts (embeddings, neural networks)
* Experience with git (push, pull, merge)
* Understanding of geographic information systems (GIS) is a plus
* Confident in working in English
* Strong organizational and communication skills.
* Proficiency in Microsoft Office Suite (Word, Excel, PowerPoint).
* Innovative Projects: Engage in impactful research.
* Global Collaboration: Work in an international, diverse team.
* Extensive Networks: Access local and international scientific networks.
Isaac Boates
isaac.boates@eifer.org