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interdisciplinary collaboration with researchers, institutions, and stakeholders Candidate Profile Required Qualifications PhD in Remote Sensing, Geospatial Sciences, Environmental Science, Climate Science, Data
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future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a meaningful
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catchment hydrology, remote sensing, or climate impact assessments. Candidates with interdisciplinary backgrounds are welcome, but strong data-analytics skills and solid knowledge of process-based numerical
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future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a meaningful
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/Offerte_di_lavoro_FBK_is_looking_for_a_Researcher_i… Requirements Research FieldOtherEducation LevelPhD or equivalent Specific Requirements The ideal candidate must have the following requirements: PhD degree, preferably in the field
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. • Proficient communication skills. • Track record of conducting original research and publishing in peer-reviewed scientific journals. Preferred Qualifications • Experience in remote sensing or machine learning
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 3 months ago
-peter-lab-index.html Your tasks Building large scale foundation models Applying and further developing single cell segmentation methods Supervising a small team of PhD and MSc students Developing new
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Phenomic prediction programs that incorporates genotype (genotype by sequence) and phenotype data (from traditional and high throughput, remote sensing sources) -Use or develop R programming code to complete
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measurements; Collaborate with multidisciplinary teams to integrate remote sensing data with field observations and other datasets; Publish research findings in high-impact peer-reviewed journals and present
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the core research activities of the project. Responsibilities include assembling and harmonizing large datasets from experimental trials, remote sensing, soil health databases, and farmland markets