37 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at Leibniz in Germany
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Physical Oceanography and Instrumentation, Marine Chemistry, Biological Oceanography, Marine Geosciences, and Marine Observations works interdisciplinary within a joint research program. What will be your
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completed scientific university education (Master's/Diploma) with PhD in horticulture sciences, agricultural sciences, biology environmental protection or a related field in-depth knowledge of organic
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, Environmental Sciences, Computer Sciences Proven experience in financial economics, financial risk assessment as well and in climate and ESG ris Interest to work at the interface between research and policy, and
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or Python Machine learning methods (for the baseline prediction for the reward funds) is beneficial We expect: Strong motivation to contribute to policy-relevant research Strong interest in teamwork and
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Your Profile Doctorate (PhD) in Ecology, Soil Ecology, or a closely related discipline Expertise in identifying soil invertebrates Experience with the analysis of food webs or trophic interactions
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phenotyping, including image analysis evaluations, for trait quantification Handle NGS datasets for RNAseq or SNP detection and linkage analysis using R Your qualifications and skills: You have a PhD or
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collaboration and mutual learning access to high-performance computing a chance to contribute meaningfully to an ambitious research agenda focused on creating positive impacts for global society and future
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assistants Your profile: PhD in social, I/O, or experimental psychology experienced in experimental research Interest in designing online interventions Profound knowledge of English Please contact Prof. Dr
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Partnership Your qualifications: PhD in environmental / agricultural science, (rural) sociology, human geography, political sciences, or related subjects Knowledge of transdisciplinary approaches and methods in
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, aggregation, linking and retrieval of comprehensive heterogeneous and distributed data sources. To this end, both statistical and linguistic analysis methods (NLP) as well as machine learning in combination