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the perspective towards generating data for entrepreneurial seed funding (GO-Bio etc.) for a further development of the technology towards the market. In that sense we also highly encourage candidates that would be
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. The research unit Intelligent Systems (IS) in Computer Science is focused on the development of Data Science, Pattern Recognition and Machine Learning algorithms for interdisciplinary data analysis. For more
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for a pre-doctoral academic with an interest in primary care cancer diagnosis and will lead to skills development particularly in analysis of observational data and may lead to opportunities to employ
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viability using multiple detection techniques (FACS, microscope, spectrophotometer). Collaboration on the analysis of created bacteria in Zebrafish models. Analyse data, contribute to scientific publications
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science, data analysis, socio-economically-driven decision-making, and collaborative research, highly sought-after skills. Number Of Awards: One Start Date: Autumn 2025 Award Duration: 4 years Application
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such as scRNA-seq, bulk RNA-seq, DNAm analysis, proteomics and clinical data integration to determine how IFN-I responses change during ageing. Application Procedure Applicants should submit a cover letter
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welcome) Entgeltgruppe 13 TV-L/75% to be filled. Starting date is 10/1/2025. The position is for three years. The positions are advertised as part of the Research Training Group 2491 "Fourier Analysis and
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of techniques for the analysis of topological data. Targeted activities in the field of public relations are also planned. The activities will mainly be based at the Institute of Scientific Computing
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. The research unit Intelligent Systems (IS) in Computer Science is focused on the development of Data Science, Pattern Recognition and Machine Learning algorithms for interdisciplinary data analysis. For more
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• Competences in quantitative research methods – ideally knowledge of several of the following aspects of quantitative data analysis: experimental research designs, survey design, large/longitudinal datasets