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-scale screens to study fundamental principles in molecular and complex trait genetics using microbes as model systems. Our core technology MAGESTIC (https://doi.org/10.1038/nbt.4137 ), a CRISPR/Cas9-based
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consortium SynThera funded by the Carl Zeiss Foundation (www.synthera.eu/ ). We are seeking an excellent and enthusiastic post-doctoral researcher with a strong interest in computational microbiome research
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data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms to understand
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proteomic analyses often obscure the intricate cellular and molecular variations within this complex environment. Single-cell proteomics (SCP) offers a novel approach to dissect this heterogeneity by
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skills in data analysis, machine learning, as well as in mathematical and computational modelling? You will have the opportunity to investigate innovative solutions using machine learning algorithms and
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Performs a variety of moderately complex research tasks determined by the field and scope of the particular research project/study. Performs tasks related to the research project independently, but
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prostate tumor samples. This position requires a strong background in both experimental proteomics and computational data science (R and Python), with an emphasis on LC-MS/MS workflows and long-term cohort
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that will be affiliated with one of six possible multidisciplinary projects. The ideal postdocs will have expertise in some of the following areas: computational modeling, computational biology, computational
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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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the view of physics aiming for identifying principles behind complex systems. We collaborates closely with engineers, immunologists, and clinical microbiologists on campus. Within this project we will