Geospatial Deep Learning Scientist II

80%-100%, Zurich, fixed-term

We are looking for a Geospatial Deep Learning Scientist with a methodological focus on AI/deep learning to join our ambitious SEED team in the Crowther Lab and help to develop and feed a growing number of models that quantify ecosystem health worldwide.

Project background

Crowther Lab is an interdisciplinary team of scientists studying ecosystems at a global scale to understand the relationships between biodiversity and climate change. Our research at ETH Zurich aims to generate a fundamental understanding of the living components of our planet that drive global biogeochemical cycles that govern the stability of our natural systems.

Within the Crowther Lab, we are launching SEED Biocomplexity in order to standardize the measurement of biodiversity at global scale. SEED integrates diverse geospatial data sources and makes use of the latest machine learning (ML) models for Earth observation (EO) data and biodiversity analysis.

Job description

Your tasks will include: designing and training EO-driven AI/ML models for automated monitoring of biodiversity in response to land-use practices, feature engineering from global EO layers, curating data sets for model training and validation, integrating model outputs within the SEED biocomplexity pipeline and contributing to the overall development of this pipeline, and staying up-to-date on recent developments in the fields of EO, ML, DL and AI. The ideal candidate will work well within a diverse team composed of ecologists, geospatial information scientists, data scientists, and software engineers.

Your profile

Desired skills and qualifications:

• A postgraduate degree and/or 3+ years working experience in geoinformatics, remote sensing, data science, computer vision, environmental sciences or similar disciplines.
• A solid understanding of common machine learning strategies (e.g., cross-validation, feature engineering, hyperparameter tuning, kernel methods, accuracy assessment)
• Proven experience in deep learning (DL) based image segmentation and object detection on EO-data (PyTorch, Keras/Tensorflow)
• Fluency in using Python for geospatial and ML applications (e.g. geopandas, rasterio, xarray, scikit-learn), plus familiarity with standard geospatial tools (e.g. gdal, PostGIS, QGIS, SNAP)

Your workplace

Your workplace

We offer

• 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
• Learning and development opportunities within and outside our organization
• Various employee perks including personal development budget

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We value diversity

In line with

our values

, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our

Equal Opportunities and Diversity website

to find out how we ensure a fair and open environment that allows everyone to grow and flourish.

Curious? So are we.

We are looking forward to receiving your application. Please include a

• Cover letter
• Curriculum Vitae
• List of references
• [If available] A link to public reference code (e.g., via a GitHub repo or Kaggle profile) or your most relevant publication

Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.

Further information about SEED can be found on our website . Questions regarding the position should be directed to Dr. Robert McElderry, [email protected] (no applications).

For recruitment services the GTC of ETH Zurich apply.

About ETH Zürich

ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow.