246 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"DFG-TRR" positions in Switzerland
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for further information) Scan of your validated UZH Card Letter of invitation or research plan Depending on the type of activity applied for, we require either a letter of invitation or a research plan. Letters
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We look forward to receiving your online application including a: CV publication list statement of research interests and the names and contact information of at least two references. Please note
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, including data management and the maintenance of computational infrastructure and software. Project background The position is part of the Institute of Microbiology at ETH Zurich and closely linked
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range of topics related to imaging with geophysical data. Our research focuses on mathematical methods for processing, imaging, and inversion of geophysical data, the physics of wave propagation, and the
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, Biostatistics, Software Engineering, Systems Operations, and Screening & Lab Automation. Embedded in this multi-disciplinary environment, the Software Engineering group builds data-centric software products
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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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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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stage, nor is it intended to support doctoral dissertations. We also encourage small interdisciplinary teams of up to three people to apply with a joint project. Please find more information here about
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therapies. Project background We are seeking a highly motivated Bioinformatics Scientist / Data Scientist to conduct multi-omics data analysis. This individual will play a key role in analyzing high
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industrial partners to tackle advanced modelling, simulation, sensing, and data analysis challenges in engineering systems across sectors. Project background The COMBINE Doctoral Network aims to train a cohort