201 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Dr" "Helmholtz Zentrum Hereon" uni jobs at ETH Zurich
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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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for the physically informed processing and joint analysis of time-series data. The successful candidate will conduct observational programmes with the SPECULOOS facility and actively participate in the scientific
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Required Experience: PhD in Geodesy, Geomatics, Aerospace Engineering, Signal Processing, or a related field Proven experience in GNSS data analysis and processing Very good programming skills (e.g., Python
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for such purposes in a wide spectrum of industries, with significant breakthroughs in computer vision, natural language processing, and intelligent control. This PhD project aims to develop foundation models (FMs
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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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60%-80%, Zurich, fixed-term Are you an ambitious data scientist with strong analytical and numerical skills, and expertise in geomatics, remote sensing, and data processing? We invite you to join
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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
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information on NSM and its research and infrastructure can be found on our website . Questions regarding the position should be directed to Prof. Andrey Zheludev, email: zhelud@ethz.ch (no applications). Please
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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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on our work and constantly improve it. We believe that the world can be improved with open data. Project background As part of our Open Science team, you will support us in developing efficient data