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collaboration with survey providers in Denmark and Germany. Analyzing survey data using quantitative methods such as conjoint analysis, regression modeling, and causal inference techniques. Writing academic
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performance of other duties. Formal requirements Applicants should hold a Ph.D. in Forestry, Ecology, Environmental Science, or a related field. We are seeking a highly motivated and ambitious individual with
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include data science management and development of novel and executing existing computational methods including machine learning and deep learning methods to integrate genomics, transcriptomics and
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or as soon as possible thereafter. The successful candidate will be working on statistical methods, scientific programming and analysis projects together with external collaborators and together
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criteria Employment as a postdoc requires academic qualifications at PhD level. Applicants must have specific theoretical and methodological competences in research on digital media and communicative
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have to: Participate in formal pedagogical training program for assistant professors. Participate in annual evaluations and a mid-track appraisal. After no more than six years of employment and on
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international, regional, and national routes to accountability and remedy for victims and the successful candidate will join the MERCURY team in applying a ‘mixing methods’ methodological approach where we employ
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Christian Lyhne Ibsen (cli@faos.dk ). Qualifications We seek candidates with the following qualifications: A PhD in Political Science, Sociology, Political History, or a related field (completed or near
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production, as well as maintenance, troubleshooting and development of systems and methods. We are looking for an enthusiastic employee with the following competencies and experience: Relevant academic degree
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. Profile We are looking for a highly motivated and skilled candidate with a PhD degree in bioinformatics or similar field. Prior experience with machine learning and protein structure modelling is expected