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Field
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, diet, and immune system to investigate their roles in various diseases, including but not limited to cancer, metabolic disorders, and infections. The research design involves the integration of large
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-impact questions in genome biology. Our Unit is at the forefront of understanding how molecular information (DNA, RNA, proteins, metabolites) is regulated, integrated, and reshaped within cellular and
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extraction, sequencing library preparation, Hi-C, ATAC-seq etc.) Experience with bioinformatic analysis of large sequencing data sets Strong statistical skills using R Desirable: Experience with assembly
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and do experiments at large facilities. Time-resolved scattering experiments allow us to monitor rapid structural changes. These experiments are complemented by laboratory methods, such as atomic force
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systems or the use of non-renewable raw materials in the global south. Large international networks provide support in working on these topics of high global relevance with the relevant partners from
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. The Applied Machine Learning (AML) group is part of the Department for Artificial
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technology Qualified support through your scientific colleagues The chance to independently prepare and work on your tasks Flexible working hours as well as a reasonable remuneration A large research campus
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lines; generation of samples for proteomics analysis Data integration and analysis, including transcriptomic, proteomic and library screen data Target validation by CRISPR-Cas9 knockouts in primary AMLs
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with: A large research campus with green spaces, offering the best possible means for networking with colleagues and pursuing sports alongside work Comprehensive training courses and individual
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neurons in the brain gives rise to the plethora of animal behaviors. Our research spans a large range of scales from the nano-scale imaging of brain circuitry, to large-scale functional imaging of brain