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Max Planck Institute for Plant Breeding Research, Köln | Koln, Nordrhein Westfalen | Germany | about 2 months ago
for ATAC, transcriptomics and multiomics assays Quality control of cells and nuclei (e.g. microscopy, Luna cell counter) User support and expert advice on experimental design, data analysis and
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Hutch is the only National Cancer Institute-designated cancer center in Washington. With a track record of global leadership in bone marrow transplantation, HIV/AIDS prevention, immunotherapy and COVID-19
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strong research capabilities with a deep understanding of trading to design, validate, backtest, and implement statistical and advanced machine learning models. Your work will span a range of initiatives
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related discipline. A professional pharmacy degree (PharmD or MD) would be preferred but not required. Applicants with experience with clinical research including prospective study designs are encouraged
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early postnatal life. This is based on the understanding that early experience shapes the way our brain is constructed. While the “ground plan” of the brain is genetically determined, it is also
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understanding, capabilities and innovation, while inspiring and providing broad training to the next generations of researchers. Our values are Commitment, Collaboration and Transformation. Our research lines
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collaborative project that spans multiple continents. You will contribute to the development of new chronobiological analytics on existing data, design experiments to collect novel chronobiological data, engage
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, staff, and student communities, and articulates that commitment in the UW Diversity Blueprint (http://www.washington.edu/diversity/diversity-blueprint /). Additionally, the University's Faculty Code
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well as to drive impactful research and innovation. PolyU will strive to continually excel as an innovative world-class university that makes a positive impact on society, living up to the University’s motto
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computational modelling to be used to design and re-engineer flower architecture. The RA's main focus will be on computational modelling of gene regulatory networks for predicting the mechanisms leading