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researcher network. The department consists of nine research sections with around 350 highly skilled employees, of which approximately 50% are scientific staff. More information can be found here . We believe
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Software Engineer - Image Quantification and Artificial Intelligence (IQAI), Department of Radiology
technical autonomy. You will be responsible for engineering the core imaging data science infrastructure that powers our clinical and research missions. In addition to collaborating on high-impact AI research
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academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and
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computational methods and algorithms for genomic sequencing data analysis, particularly in the context of genome assembly. This is an exciting opportunity to develop novel computational approaches for microbial
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high-throughput workflows, including single-cell proteomics. It operates state-of-the-art instrumentation and advanced data analysis pipelines within the multidisciplinary ecosystem of Human Technopole
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the Quantum Optics, Quantum Nanophysics & Quantum Information group at the Faculty of Physics, and a member of the Vienna Center for Quantum Science and Technology (VCQ) - one of the largest quantum hubs in
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academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and
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, and data science and further develop this expertise in the context of living lab research. The new organizational unit will also cooperate closely with ZALF's existing research areas and service
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financial information systems. Experience with accounting standards and regulations (e.g., IRS, US GAAP, Uniform Guidance, hospital regulations) within a specific area. Experience working with cross
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Faculty Positions in Genomics and Bioinformatics at the Institute for Genome Sciences, University of
biology, bioinformatics, biostatistics, bioengineering, computer science, mathematical biology, or a related discipline, with a strong background in analyzing and integrating tumor biology and clinical data