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. What you will do As a postdoc in our group, you will set up and lead this new research line, choosing its directions together with us. Possible starting points are the formalization in Lean of
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in at least one programming language for geospatial analysis: Python (rasterio, geopandas, scikit-learn), R or Google Earth Engine. Experience with open-source tools (QGIS, GRASS GIS, GDAL) and
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Chemistry group at ETH Zurich ( https://reiher.ethz.ch ), led by Prof. Markus Reiher, which will perform detailed quantum-chemical calculations of reaction rates. The research will develop along two
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, resilience, and ecosystem functioning. Using enrichment cultures combined with metabolite profiling and multi-omics analyses, our group has recently revealed that: (1) environmental selection imposed
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, tokenization, and scalable architectures that integrate diverse biological data modalities. Multimodal representation learning: aligning and fusing information across modalities to capture biological systems
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demanding environments such as space systems, cryogenic applications, ultra-clean settings, microelectromechanical systems, and surgical instruments. Their main advantages include frictionless
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level of dedication and work ethic are essential. Prior experience with animal models, 3D culture systems and/or computational analyses will be an advantage. The salary will be according to EPFL
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data modalities. Agentic interfaces: integrating foundation models into reasoning and decision-support systems. Translational applications: bridging foundation model research towards impact in early
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screening platform from the ground up, with significant ownership over pipeline design Access to the lab's existing imaging/biophysics infrastructure and tissue-engineered infection model systems Integration
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molecular and optical technologies to study mechanisms of cell surface signaling, cancer neuroscience, and protein engineering, integrating molecular biology, cell biology, and systems neuroscience