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Max Planck Institute for the Study of Religious and Ethnic Diversity, Göttingen | Gottingen, Niedersachsen | Germany | 20 days ago
itself can sustain or undermine institutions. The department’s empirical focus is on the Global South and combines advanced quantitative methods, such as survey-based and observational causal inference
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topics, within a department that has a strong track record in AI research. Applicants for the associate position should have already completed, or be close to completing, a PhD in a relevant discipline
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of infectious diseases. • Experience with data analysis using statistical inference techniques. • Experience with health economic evaluations. • Experience with parallel and/or high-performance computing
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topics, within a department that has a strong track record in AI research. Applicants for the associate position should have already completed, or be close to completing, a PhD in a relevant discipline
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PhD Expert knowledge of statistical modelling, statistical inference and use of relevant software (e.g. R/Python) both for data processing, visualisation and programming. Excellent communication and
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transfer learning for distributed and privacy-preserving data integration. AI and Deep learning approaches to high-dimensional and multi-modal biomedical data. Causal Inference, Fairness, and Trustworthy AI
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and Causal Inference for Public Health and Education Research (NCIPHER) lab at the College of Pharmacy at the University of Rhode Island invites applications for a postdoctoral fellow to conduct
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health metrics using large datasets and causal inference techniques Evaluating welfare gains and resource allocation in health Improving health system productivity through economic analysis Forecasting
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Transparency, and Societal Impact. Candidates should bring expertise in areas such as: Causal inference and the design and analysis of experiments Reinforcement learning and sequential decision-making Analysis
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analysis of models Alignment and language model agents Other backgrounds that could inform language model interpretability and control, such as cognitive science, neuroscience, causal inference