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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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on the following activities: Writing scripts for the automated collection and cleaning of data, and organizing it into a database Computing simple statistics Preparing graphical representations Testing surveys
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health. We are looking for a proactive and skilled Software Engineer to join the newly forming research group Analytics and Informatics for Child Health (AICH) at the Department of Biomedical Engineering
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on Human Factors in Computing Systems, Lancet Digital Health, npj Digital Medicine). You will also be involved in teaching activities.
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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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multidisciplinary research program and collaboration network in the area of Culturomics. Promising candidates possess an interdisciplinary profile that combines outstanding microbiological expertise with excellent
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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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Your profile Candidates should have an exceptional academic record and a robust mathematical foundation. They should have published works at the main conferences in the field of machine learning, such as ICML, NeurIPS, ICLR, etc. Excellent communication skills and fluency in English (spoken and...
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, middle eastern studies, political science, sociology, gender studies, see also: g3s.unibas.ch ). They may likewise be trained in interdisciplinary fields also represented at G3S: • PhD Program Gender
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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