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strategies. We develop new methods with which tumors can be diagnosed more precisely and cancer patients can be treated more successfully. Every contribution counts – whether in research, administration
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new method for lncRNA gene identification from whole genome sequences. Collaborating with experimental researchers to integrate computational findings/tools with functional investigation. Scientific
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understanding and knowledge of climate dynamics. The candidate should have experience of statistical (multivariate) concepts and should be open to apply new and upcoming AI methods to analyze the climate
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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biology, computational biology, in vivo models of disease, and pre-clinical study development. You will have the opportunity to develop and lead projects using several cutting-edge model systems including
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HPLC and other chromatographic methods) High competence in structure elucidation of natural products (1D and 2D NMR, HRMS, other spectroscopic and computational methods) Experience in writing first
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products (1D and 2D NMR, HRMS, other spectroscopic and computational methods) Experience in writing first author-publications, high publication track record in scientific journals and conference
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of APP and other genes causing familial Alzheimer’s disease. The studies will include the design of components required for prime editing, as well as the development of efficient delivery methods. Apart
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and to identify new therapeutic targets and prognostic biomarkers. Novel data integration methods allow to identify signatures of retinal cell types in liquid biopsies without the need for a direct
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2019 https://doi.org/10.1038/s41596-018-0110-x and Lara et al., arXiv:2503.21396 https://doi.org/10.48550/arXiv.2503.21396 )). In parallel with your experimental work, you would develop theoretical