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neuropsychological methods and large-scale cohort studies to advance mechanistic resilience research in the field of cancer survivorship. To strengthen the team in the Division of Cancer Survivorship & Psychological
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collaboration in research networks Your profile PhD in Bioinformatics, Computational Biology, Systems Biology, or a related discipline Experience in multi-omics data analysis and handling big data Experience with
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Biology, or a related discipline Experience in multi-omics data analysis and handling big data Experience with single-cell and spatial transcriptomic analyses is a plus High motivation and curiosity
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dynamics, in particular for very large fires. A special focus lies on extreme events and rapid changes. We want to test if our current climate and vegetation modelling tools can reproduce the past
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participate in scientific discussions and team meetings Taking over project responsibility Collaborating closely within an interdisciplinary research team and a sincere interest in analysis of large scale data
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conferences and the preparation of project reports. Develop and apply software tools. Documentations of software and data according to the FAIR data principles. Contributions to workshops and training
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reports Develop and apply software tools Document software and data according to the FAIR data principles Contribute to workshops and training activities Your Profile: Master with subsequent PhD degree in
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large multi-dimensional datasets using statistical tools such as positive matrix factorization (PMF) and cluster analysis Investigate the influence of different urban emission sectors on atmospheric
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Heidelberg University and Stanford University, including population health researchers, clinicians, and methodologists. The researcher will lead analyses in large-scale electronic health record data
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of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning