Master's thesis: Machine learning and Earth observation data for mapping Swedish wetlands
Technology, Data & Digital · Data, AI & Analytics · Machine Learning · Data Science · Data Analysis
In short
Responsibilities
- Develop and train machine learning models for mapping Swedish wetlands.
- Process multimodal satellite images (e.g., high-resolution aerial orthophotos, DEM, Sentinel-1 and -2 data).
- Apply novel deep learning methods for fine-grained mapping of Swedish wetlands.
- Utilize computer vision models such as convolutional neural networks and vision transformers.
- Implement various data-efficiency techniques within ML.
- Work within a multi-disciplinary team including ML and biodiversity experts.
Requirements
- Experience of implementing machine learning, especially deep learning, models.
- Completed courses in machine learning, image analysis, or similar.
- Programming skills, preferably with experience of relevant frameworks such as Pytorch or JAX.
Desired Qualifications
- Courses in GIS, remote sensing, or similar are preferred.
- Experience with geospatial data processing, e.g., QGIS, GDAL, Geopandas, Rasterio is preferred.
Benefits
- Opportunity to reach a high level of research excellence.
- Potential for a joint research paper in addition to the Master's thesis.
- Thesis project with a research organization (RISE).
Skills
As the challenges facing us as a society become increasingly complex, innovation alone is not enough; you need a strong innovation partner who can provide comprehensive support and a broad range of perspectives. This is where RISE comes in. RISE is a unique mobilisation of resources to increase the pace of innovation in our society. By gathering a number of research institutes and over a hundred test beds and demonstration environments under the umbrella of a single innovation partner, we create improved conditions for society’s problem solvers. We gather around challenges and organise…
Job Posted
3 days ago
Employment Type
Internship
Work mode
On Site
Experience Level
Student
Locations
Lund, Sweden
Qualification
Applicants
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