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Field
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microscopy methods such as light-sheet fluorescence microscopy (LFSM) and the experience in computational data science to handle the resulting large 3D datasets. We are looking for an enthusiastic and creative
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large pan-European research initiative that brings together researchers, clinicians, and patient communities. Your project focuses on analyzing multi-omics sequencing data from thousands of patients with
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- Practical experience in working with RNA (RNA extraction, RT-PCR, RNA sequencing) - Knowledge in programming languages like R or Python for data manipulation and analysis - Experience in quantifying plant
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Artificial Intelligence) is being expanded into a leading German AI competence center for Big Data and Artificial Intelligence (AI). TUD Dresden University of Technology embodies a university culture that is
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that you have to work with large datasets, from i.e. semi-quantitative LC-MS/MS proteomics, therefore proven affinity with R is an asset. You will work here The research is embedded within the chair
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at the interface of data science and the scientific domains pursued at the three participating Helmholtz centers. Methodologically, a broad range of topics is covered, from large-scale data management to data mining
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of data structures, static analyses and compiler optimizations, parallelism and concurrency) to turn these new theoretical developments into performant implementations; building state-of-the-art
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large international community and a lot to offer to international employees. Because we expect you to work and live in the Netherlands our team of advisors on Dutch immigration procedures will help you
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on an exciting Wellcome-Trust funded project. The research focuses on decoding neural representations across dynamic brain states through advanced computational analysis of large-scale neural recordings. What you
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analyses using your own data and large public data resources and integrate your findings with clinical data (symptoms, EEG, etc). Finally, you will contribute to other activities of the STXBP1 team