242 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"Edinburgh-Napier-University" positions in Switzerland
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models or glioblastoma research Familiarity with transcriptomic methods (RNA-seq, FISH, spatial transcriptomics) Programming skills for data analysis (Python, R, or MATLAB) Workplace Workplace We offer
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Health (AICH) group develops AI/ML methods, digital tools, and secure data pipelines to advance pediatric healthcare. We work at the intersection of clinical medicine, machine learning, and data-intensive
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multimodal data analysis, with an initial focus on neuroscience. To build this interdisciplinary platform, we invite applications for three PhD-level Research Specialists: Microscopy and Spatial
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frames). Project background The work focuses on data-driven generation of structural systems. You will be involved in developing, experimenting with, and evaluating machine learning models that help
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: Literature and data reviews for STES technologies and projects Data processing and analysis Techno-economic and environmental analysis Preparing presentations and project reports in German and English
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strengthen host communities. You will work on a quantitative research project that contributes to this mission. The project uses large-scale click data from an online job platform and administrative data
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vision and its associated diseases, as well as to develop new therapies for vision loss. For more information, please visit iob.ch ! About the project For a project in the Human Retinal & Central Visual
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year, with a prospect of becoming indefinite) on the development of the data-analysis suite and pipeline infrastructure for the upcoming gravitational-wave space observatory LISA. In 2015, the LIGO–Virgo
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The primary focus of this position is the project-specific analyses of diverse high-throughput multi-omics datasets, encompassing a broad range of data types such as whole-genome and transcriptome
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problems in scientific or engineering domains using proprietary/real data (beyond public benchmarks), where challenges like distributional generalization, multi-objective trade-offs, causality, privacy