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. Extensive experience in scientific computing involving programming, numerical analysis, symbolic and logical analysis, Monte Carlo simulations, and computer graphics. Experience in Matlab, Mathematica
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record of hands-on research, ideally in mammalian cell culture and engineering, molecular biology, or synthetic biology Desirable: Experience with genomic data analysis, automation platforms
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the Human Pancreas Analysis Program (HPAP) and related consortia, providing access to deeply phenotyped T1D samples, islet organoids, and rich multi-omic datasets. Key Responsibilities Design and
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Automated (Syncropatch384, Nanion) and manual patch-clamp experiments High-throughput spinning disc confocal microscopy (Yokogawa CQ1) Data analysis Your qualifications Excellent and highly motivated
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the department and across the university and join a cross-institutional research team focused on neuroscience, aging, and -omics data analysis. Responsibilities Develop and apply innovative machine learning
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to integrate multi-omics datasets and link epigenomic evolution to emerging phenotypes Use high-throughput CRISPR perturbation screens in cerebral organoids to test the functional relevance of candidate elements
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dependence on imported rare earth elements while minimizing environmental impact and industrial waste. Through innovative recycling and material recovery methods, this research fosters Climate Resilience
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of magnetic materials and devices. In addition, we conduct collaborative research with other research groups within NIMS specializing in microstructural analysis and theoretical calculations, as well as with
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knowledge on multi-actor collaboration, networking and bridging, the applicant will conduct ecosystemic analysis and initiate interventions, measure synthesis, dead-ends and resistance and, in comparison with
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