265 data-"https:"-"https:"-"https:"-"https:"-"Academia-Sinica" positions in Switzerland
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are considered during the evaluation of applicants of all genders. Information on your application Applicants are kindly invited to submit their applications, which should include: • a cover letter (max. 1 page
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processing (experimental planning, setup, measurements, analysis) Conceptualization and realization of novel setups (hardware integration, optical setups, etc.) Software development (data acquisition and
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publications for this position highlighted Reference letters and/or contact details for three academic and/or professional references (You will be notified before they are contacted) Further information about
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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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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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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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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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interdisciplinary and multicultural research teams, bridging the gap between data science and energy engineering Proficiency in English is required Workplace Workplace We offer A young, dynamic and interdisciplinary
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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
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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