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levels. In this project, the PhD student will learn to understand and apply modern causal inference techniques such as target trial emulation, marginal structural models and G-computation to observational
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inferences are also made from mechanistic insights from animal studies to human medicine. Moreover, the project reflects on the implications of different experimental designs for knowledge generation
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in the field of Battery Technology with a strong emphasis on AI. An ideal candidate is expected to have an excellent track record in most of the following topics: Battery Technology Characterization
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engineering that is obtained after 2016. Excellent scientific track record Prior experience in 2-photon microscopy imaging in live mice and / or visual cortex is preferred Experience in Matlab programming and
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data (e.g., GLM, RSA), or EEG/MEG data (e.g., source modeling, DCM). A strong track record of publications in psychophysics, perceptual decision-making, and/or neuroimaging in internationally recognized
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excellent track record and will be a highly motivated self-driven candidate with a PhD and at least 4 years post-doctoral experience in the field of Parkinson’s disease. You have a deep understanding of the
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methodologies in machine learning and causal inference applied to human health. Read more about NCRR here . Your job responsibility With a motivated, interdisciplinary team of approximately 70 researchers and
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methodologies in machine learning and causal inference applied to human health. Read more about NCRR here . Your job responsibility With a motivated, interdisciplinary team of approximately 70 researchers and