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at ETH Zurich and associated with the ETH AI Center. We are an interdisciplinary group at the intersection of chemistry and computer science. Our mission is to accelerate chemical discovery using digital
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scientific and engineering computing, and explores commercial pathways for software innovations. If you are looking for a role that blends technical excellence, leadership, and business strategy, we would like
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approaches specifically addressing the health challenges faced by children and adolescents globally. The BRCCH is located in Basel, at the heart of the leading Life Science cluster and offers excellent
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afterwards. You will work closely with our research team to implement a new version of our RAG-based chatbot. Profile The ideal candidate will be a computer or data science student, or a student with extensive
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utilises cutting-edge recording techniques, including two-photon calcium imaging, high-density Neuropixels electrophysiology, and spatial transcriptomics, alongside computational analyses, to uncover novel
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, Environmental sciences, or a closely related field. Proficiency in programming, particularly in Python, is essential. Knowledge of GIS (QGIS or ArcGIS). Experience working with spatial data, shapefiles, raster
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Your position Our group conducts research at the intersection of artificial intelligence (AI) and pediatric healthcare, developing AI and machine learning (ML) methods to address real-world clinical challenges. Our core research topics include but not limited to the following...
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(SCI), lower back pain, neuro-degenerative disorders and neurological tumors. At the core of our research is the collaboration across disciplines spanning expertise in medicine, biology, computer and
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80%-100%, Zurich, fixed-term The Department of Computer Science at ETH (D-INFK) is offering a new Master of Advanced Studies (MAS) in AI and Digital Technology. This is a continuing education
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Emulators of Stochastic computational models"), funded by the Swiss National Science Foundation (SNSF). The project aims to significantly advance the state-of-the-art in uncertainty quantification (UQ) by