Geospatial Machine Learning Scientist

vor 2 Wochen

Munich, Deutschland The Landbanking Group Vollzeit

The Landbanking Group’s (TLG) mission is to completely transform the way we use land in these unprecedented times of accelerating climate change, mass extinction and social divide. A novel, globally active company was founded to turn landowners and land stewards into producers and sellers of ecosystem services and products. TLG integrates diverse geospatial data sources and makes use of the latest machine learning (ML) models for earth observation (EO) data, carbon footprint and biodiversity analysis. Combined with scalable ground-based assessments, e.g. metagenomics, bioacoustics, we develop digital twins of land plots, assess ecosystem quality, verify proof of impact and tokenize the claims so that they can be traded or bundled into tradable assets. TLG is now looking for a Geospatial Machine Learning Scientist (gn) with a methodological focus on EO data processing, supervised classification and rule-based processing to join our ambitious team and help to develop and feed a growing number of models that quantify ecosystem health and ecosystem services worldwide. **Your tasks**: - Design and train EO-driven ML models for automated monitoring of land-use practices, habitats and ecosystem health, e.g. landcover classifications, crop type mapping, derivation of phenological metrics or biophysical indicators - Calculation of landscape indicators from map products such as habitat fragmentation, human impacts, landscape diversity. - Integrate existing processing systems (e.g. cloud masking modules) through wrapping in our pipeline. - Curate training data sets and design sampling strategies for ground data collection or custom labelling. - Package fitted models into containerized pipelines for deployment by the engineering team. - Stay up-to-date on recent developments in the fields of EO, ML and AI and feed back into internal model feasibility assessments and product roadmap planning. - Contribute to research and development activities of associated academic partners - A postgraduate degree or >3y working experience in geoinformatics, remote sensing, environmental sciences, geoecology or similar disciplines - Knowledge of current space-borne EO missions, their characteristics and pre-processing requirements (optical, SAR, LiDAR, thermal missions) - A solid understanding of common machine learning strategies (e.g. cross-validation, feature engineering, hyperparameter tuning, accuracy assessment) - Familiarity with Linux environments (e.g. docker, bash, AWS) - Ability to do rapid prototyping in GEE whilst being able to implement the same analyses using open toolchains within our own infrastructure (STAC etc.) - Flexibility to travel and work temporarily on site with associated academic institutions **What's in it for you?**: - Impact - A working environment based on trust, encouragement and feedback - A positive, inspiring and truly interdisciplinary work atmosphere - High degree of autonomy - Competitive salary - Challenging and novel problems to solve - Work remotely (timezone should be close to Germany) - Learning and development opportunities within and outside our organization - Various employee perks including personal development budget

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