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computational experiments and data pipelines Experience analyzing complex experimental data and large-scale datasets using advanced quantitative and statistical methods Track record of independent scientific
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experimental workflows A sound understanding of demagnetisation procedures, magnetic-property measurements, data processing, uncertainty, quality assessment and interpretation Experience with quantitative data
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, motivated, and enthusiastic candidate with a keen interest in evolutionary questions and a strong background and hands-on experience in experimental molecular and genomics approaches. Additional experience in
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building experimental setups, rapid prototyping & technologies such as stereolithography, two-photon printing or nano-imprint lithography is highly desirable Experience with scientific computing and
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computational biology across the university and affiliated institutes, as well as with experimental researchers (wet lab) in the AG Laugsch, to support accurate data interpretation and integration Maintain clear
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) Interest and ideally experience in microbiome omics (16S/shotgun; analysis or interface expertise), ideally knowledge in bioinformatic pipelines Solid experimental design and data analysis skills (R/Python
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the university and affiliated institutes, as well as with experimental researchers (wet lab) in the AG Laugsch, to support accurate data interpretation and integration Maintain clear documentation of analyses and
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, bioinformatics, systems biology, computer science or related field Strong proficiency in Python and/or R Experience in single cell omics analysis and multiomics data interpretation Ability to work independently