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: RSnowAUT A modular remote sensing pipeline incl. ground-truth monitoring for automated snow avalanche detection and forecasting Project duration: 2022 – 2025 Development of a data pipeline that can process
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@dp-uni.ac.at Deadline: April 30, 2024 Interview for the position will be held remotely and/or in person. The exact date will be communicated as soon as the shortlist has been finalized. If you have
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of the experiments by participating in meetings remotely or in person and by contributing to the operation of the experiment · You are willing to work in an international environment which value diversityies We
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well as publication activity • Fluent command of English (knowledge of German will be an asset) • Excellent IT Knowledge (MS Office, Zoom, Adobe, GIS etc.) Our offer: • Excellent opportunities to work
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candidates who fall outside the above criteria. - Following the initial evaluation round, top-ranked candidates must be available for a remote interview between August 19 and September 05, 2024
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Additional Information Benefits What we offer: Work-life balance: Our employees enjoy flexible working hours, remote/hybrid and/or part-time work (upon agreement). Inspiring working atmosphere: You are a part
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Austrian Academy of Sciences, The Institute for Habsburg and Balkan Studies (IHB) | Austria | about 2 months ago
with learning processes in foreign policy, examining how the elites made sense and use of transnationally circulating political ideas and of observations and exchange. Third, it will systematically
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sensing, atmospheric tomography, and point spread function reconstruction. An involvement in the development of the instruments METIS and MICADO for the European Extremely Large Telescope is expected
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high social/communicative skills Additional Information Benefits What we offer: Work-life balance: Our employees enjoy flexible working hours, remote/hybrid and/or part-time work (upon agreement
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(possibly) uncountable dictionaries, so-called continuous frames by employing low discrepancy point sets. The latter are sets of points that are well-distributed in a domain of interest in the sense