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particle physics, computer science or a related field Experience with large-scale data management using grid or cloud technologies Experience in one of the on-site experiment would be an asset Familiarity
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plant development. PLoS computational biology, 15(6):e1007121, 2019. doi: 10. 1371/journal.pcbi.1007121. URL https://journals.plos.org/ploscompbiol/article?id=10.1371/ journal.pcbi.1007121 . D. E. Moulton
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | 3 months ago
23 Jan 2026 Job Information Organisation/Company Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung Research Field Environmental science Researcher Profile Recognised
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qualifications: • A completed Master’s degree (or equivalent) in a relevant discipline, such as philosophy, neuroscience, psychology, medicine, law, social sciences, computer science, or a related field • Strong
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Qualifications / Experience: A PhD degree in physics, engineering, environmental sciences, or a related discipline, is required Knowledge and hands-on experience with atmospheric lidars or other atmospheric
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social or behavioral sciences (incl. human-computer interactions with relevant experience). Applicants must demonstrate experience in experimental work with human participants; possess versatile
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) and present your work at top conferences and journals in our field. Candidates should have completed their Master/Diploma studies in Computer Science, Mathematics, Mechatronics, Electrical Engineering
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) Application Deadline 15 Feb 2026 - 22:59 (UTC) Country Germany Type of Contract To be defined Job Status Other Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the
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underrepresented groups to apply. The review process is on a rolling basis. Please refer to the “Application Procedure” section for details on how to apply. Current Openings Safety, Performance and Reliability in
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, Geosciences, Environmental Sciences, Physics or Mathematics (plus significant work experience in the field can also qualify) Understanding of hydrological processes Experience in statistics and data-driven