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advanced computational methods to uncover mechanisms of neural circuit repair and regeneration. The candidate will integrate large-scale transcriptomic and epigenomic datasets with state-of-the-art deep
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for a postdoctoral researcher with experience in computational analyses. Your mission As a postdoctoral researcher, you will: • Develop and apply bioinformatic methods to analyze alternative splicing
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appropriate treatment—ultimately saving lives. We are particularly looking for applicants with experience in prediction models and biomarker evaluation, causal inference, longitudinal methods, survival analysis
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, study design, and conducting statistical analyses and data interpretation. You will also provide advice and guidance on statistical and data science methods to the project collaborators. You will also
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methods to rigorously assess the safety and effectiveness of medications in real-world patient populations. Defining individualized treatment strategies: Leveraging traditional and causal machine learning
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. Supervise and support PhD students and junior researchers within the group, and contribute to the recruitment process together with the research group leader. Lead and coordinate project teams, collaborating
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education in Sweden. At KI, you get to meet researchers working with a wide range of specialisms and methods, giving you ample opportunity to exchange knowledge and experience with the various scientific
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splicing and computational method development. The Chen lab is interested in developing advanced computational approaches to decipher RNA diversity and its regulatory mechanisms in human metabolic diseases
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by using imaging methods to study aging and cognitive diseases. It is also expected that you will gradually initiate and run your own research projects, which can be done to some extent based on your
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lead, you will implement computational quality control and analysis pipelines for various types of omics data from clinical samples from the lung, and assist wet lab-oriented post-docs and PhD students