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GESIS - Leibniz Institut für Sozialwissenschaften | Mannheim, Baden W rttemberg | Germany | 1 day ago
, Political Science, Social Psychology, Survey Methodology) Sound knowledge in empirical quantitative social research including the use of statistical analysis methods and programs (Stata, R) Excellent
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developing generic tools that take a declarative problem description and automatically compute an optimal solution to it. Often, users specify their problem in a high-level, human-understandable formal
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evaluate existing party initiatives and best practices (3) explore to what extent formal rules and informal norms render parties ableist institutions 4) co-produce recommendations with Disabled People’s
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must be inferred from the data. The overall goal is to develop reliable and robust statistical methods that can contribute to scientific understanding and inform decision-making and public policy
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Postdoctoral position for the project Human AI Collaboration: Imaginaries, Interventions, Interfaces
full project description here, including a detailed description of SPs and WPs: https://pure.au.dk/portal/da/projects/human-ai-collaboration-imaginaries-interventions-interfaces . Information about the
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to evaluate the effects of adaptive dialogue strategies on engagement, openness, curiosity, empathy, and reflection; Contribute to reusable experimental infrastructure, datasets, evaluation methods, and
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EXPERIENCE in: Scientific/Academic writing Research methodology (Quant or Mixed Methods) Experience with statistical software (e.g., R, Mplus, SPSS, etc.) Credentials must be obtained prior to the start date
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. Hands-on experience of LC-MS and tandem MS for untargeted and/or targeted analysis. Experience developing or optimising sample-preparation methods for biological matrices. Desirable Criteria: Experience
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strategies and artificial intelligence based on chemical analysis results. The researcher will be responsible for the integration, processing, and interpretation of data, applying statistical methods and
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health, health data science, medicine, pharmacy or a related discipline. Experience analysing complex datasets using R, Stata, SAS or Python. Knowledge of epidemiological methods and healthcare data