190 data-"https:"-"https:"-"https:"-"https:"-"SUNY-Polytechnic-Institute" positions at ETH Zurich
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Computer Vision and Computer Graphics techniques to digitize human avatars and garments in 3D. Within this project, your role is to advance our existing algorithms that reconstruct 3D garments from multi
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lab / external, we are seeking a post-doctoral researcher to join our team. In the project, we will be analyzing ride-sharing, shared e-scooter and shared bicycle behaviour. We will analyse the data
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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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Academic transcripts A short statement of motivation and research interests Contact information for three references Please note that we exclusively accept applications submitted through our online
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data, spanning from whole-genome variant calling and decision support to single-cell sequencing analysis. We develop and extend robust analysis workflows and reusable components, in close collaboration
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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