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the transfer of new ideas from the lab to real-life applications, improving lives. The Computational Health Center (CHC) at Helmholtz Munich drives research at the intersection of artificial intelligence, data
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(e.g. RNAi, CRISPR/Cas9, small-molecules). In this context, we also develop new computational tools for automated analysis and data visualization. These include algorithms and software applications
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discipline The ability to independently design and execute experiments and interpret data Expertise in at least one of the following areas: Super-resolution imaging, including Stimulated Emission Depletion
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multi-omics data resources to drive innovative research REQUIREMENTS: Master’s degree (or higher) in (bio-)statistics, epidemiology, mathematics, or a related discipline Proven proficiency in R Solid
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interdisciplinary and international team of bioinformaticians, molecular biologists, and clinicians to identify (i) targetable lesions for cancer patients in high-dimensional data, including next-generation
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, close working relations, network activities among young scientists, and social activities a workplace characterized by professionalism, equality, and a healthy work-life balance Contact Information
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University with related departments. Contact information For further information, please contact Prof Kim Daasbjerg at +45 23 48 52 49 or kdaa@chem.au.dk or alternatively Associate Professor Behzad Partoon
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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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, plant transformation, plant breeding, computer vision assisted automated phenotyping, machine learning and AI. The role will require working with other institutional stakeholders to scope, design, equip
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at the Institute of Medical Informatics within the research group “Medical Data Integration Center (MeDIC)” led by Dr. Michael Storck and is embedded in the DFG-funded Collaborative Research Centre 1748, Principles