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design, development, and experimental validation of high-performance fuel cell materials. Your focus will be on optimizing electrode and membrane materials to improve reaction kinetics, structural
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bioinformatics, with a particular emphasis on performing analysis of high-dimensional data, which can be sequencing and/or imaging-based. Experience working with AI and machine learning approaches are considered a
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, the candidate will develop new computational strategies to identify human genetic variation linked to cell fate changes in neurodevelopmental disorders and cancer. The candidate can use and combine single-cell
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interdisciplinary research environments with high international impact. We perform world-class research, which contributes with solutions to solve essential societal challenges within the green transition: food
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-performance computing infrastructure, fostering an excellent environment for genomics-based research. The position is fully funded for 2-3 years with a competitive salary and benefits. For more information
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computational approaches. We are seeking a postdoctoral researcher to: Perform research on Parkinson's disease by the use of iPSCs Characterize molecular impairment in PD Become an active lab member For further
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advanced imaging techniques and high throughput single-cell technologies including high density spatial transcriptomics. As eluted to above we will have access to a unique well-characterized clinical biopsy
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differentiation protocols for iPSC perform CRISPR-based genome editing and molecular biology experiments develop and optimize high-throughput sequencing techniques work with a substantial amount of multi-Omics data
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biomedical sciences. What You Can Expect: We offer a diverse and stimulating range of tasks in the field of big data analysis, where you will develop and apply advanced computational methods to analyze complex
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Helmholtz Association of German Research Centers . Over 3,200 staff members from 88 nations are dedicated to performing and driving cutting edge research for a life without cancer. Organized in more than 100