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collection and/or experimentation. We seek candidates who have completed a PhD in ecology or a related field, have strong conceptual and statistical skills, and experience working with large and complex
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in this project. Additionally, the student will be encouraged to collaboratively contribute to the further development of these methods. The PhD student will be supervised by Academy Fellow Dr. Gleb
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on the research interests of the candidate, there will also be opportunities to complement existing data with additional field data collection and/or experimentation. We seek candidates who have completed a PhD in
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our community’s diversity and inclusiveness. This is why we warmly encourage qualified candidates from all backgrounds to join our community. PhD Researcher: AI-Enhanced Adaptive Design for Dynamic
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, at the Division of Pharmaceutical Chemistry and Technology. Our aim is to create new machine learning and artificial intelligence methods to accelerate drug development. The successful candidate will contribute
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methods (at minimum, linear regression (OLS) and logistic regression, as well as familiarity with some advanced methods). Proficiency with statistical software (e.g. R, Stata). Ability to work both
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concerned with optimal transport for inverse problems. Optimal transport for inverse problems One of the central topics of the research projects is the further development of theory and methods
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. Currently, research activities focus on applying research methods from experimental psychology and cognitive science to augment human intelligence with AI. Your experience and ambitions eligible for PhD study
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, NLP, behavioral sensing, and causal inference, the project pioneers new methods for detecting and mitigating online harms. Its results aim to inform public health, policy, and technology design
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interactive prototypes for scenario testing and stakeholder engagement. Collaborate closely with the PhD researcher to connect environmental data analysis with computational design innovation. Participate in