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scales using hyperspectral earth observation data. Within the ASCENT project, you will work as a PhD candidate in an interdisciplinary consortium with remote sensers, ecologists, data scientists, and
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LanguagesFRENCHLevelBasic Research FieldBiological sciencesYears of Research ExperienceNone Research FieldEnvironmental scienceYears of Research ExperienceNone Additional Information Website for additional job details https
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quantification and apply these methods to large-scale clinical cancer data? Are you looking for an employer that invests in sustainable employeeship and offers safe, favorable working conditions? We welcome you to
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in Finland in its area and responsible for the teaching and research in computer science at the University of Helsinki. The main research fields at the department are artificial intelligence, big data
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of these models therefore remains a key scientific challenge. In this PhD project, you will develop and apply data-fusion methods that combine physics-based wind farm models with wind tunnel and field data. A
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Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. | Dortmund, Nordrhein Westfalen | Germany | about 15 hours ago
Bioanalytics for the Multidimensional OMICS Data Analysis research group, we invite applications for a: PhD Candidate (m/f/d) This position is part of the Leibniz Science Campus “Cardio-Oncology Campus
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for the Evolutionary Understanding of Human Diseases (Apollo). Information on the department can be found at https://globe.ku.dk . Our research The APOLLO Ancient Genomics Initiative is a pioneering research program led
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4 Sep 2026 Job Information Organisation/Company Max Planck Institute for Solar System Research Research Field Astronomy » Astrophysics Researcher Profile First Stage Researcher (R1) Positions PhD
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Applications are invited from qualified individuals for a full-time tenure-track faculty position in Beef Cattle Research and Extension in the Department of Large Animal Clinical Sciences (https
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of Python and R; Knowledge of web development (Shiny or equivalent technologies); Experience processing and analysing large datasets; Experience with version-control tools (Git); Data visualisation skills