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Office, Linux proficient in dealing with operating systems and high-performance computing facilities We expect: the ability to work independently and on your own initiative a methodical and systematic
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to identify transcription-factor master regulators and derive targets for gene editing / TILLING. You integrate multi-omics data to identify genotype-phenotype associations. You ensure FAIR data management
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/ research stays, and/or presentations at international conferences; Proven experience in quantitative and/or qualitative social-science methods; Willingness and ability to further PRIF’s research agenda
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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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and apply cutting-edge methods in artificial intelligence (AI) to address urgent societal and environmental challenges such as improving food security, promoting animal welfare, protecting biodiversity
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and processing of industrial policy data and ensuring rigorous analytical methods are applied. Your Profile Required: Ph.D. in Economics Proven expertise in industrial policy research Fluent in English
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) and programming languages (e.g. Python, Matlab, R) as well as in advanced statistical methods for analyzing complex ecosystem and environmental datasets. Good knowledge of European marine ecosystems as
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the team of Prof. Dr. Loriana Pelizzon on data and methods for supervision of climate and ESG risks in Capital Markets (incl. investment funds, bonds, stocks). The role involves advising and
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research questions a strong collaborative spirit and enjoyment working closely within a diverse research team intellectual curiosity, creativity, and an openness to exploring new methods and
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in non-academic, participatory contexts and projects with their own citizen science component. Your tasks: For researchers (m/f/d) working on their doctorate: to develop a historical, cultural or