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Postdoc position on ultra-long read sequencing for animal epigenomics, transcriptomics, and genomics
to address with (ultra) long read sequencing A Curriculum vitae including a list of publications, complete academic record, and copies of Bachelor's, Master's and PhD degrees Names and contact information
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to project future forest responses to global change drivers. Job description Compilation of existing, large data sets across Europe Identification of forest resistance and resilience to deposition and climate
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to DNA damage and mutagenesis, microbial metabolism of chemicals, and precision medicine. Your profile You have experience in the evaluation and visualization of diverse large data sources
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exploring new phenomena in quantum nonlinear optics. Project background Realizing the promise of quantum technologies hinges on our ability to efficiently connect and transfer information across different
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strategies to design pulse sequences for high-resolution solid-state NMR under magic-angle spinning and static DNP in close collaboration with two PhD students working on these topics. The efficiency
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networks of living neurons, and interact with them using microelectrode arrays. This provides us with a large amount of highly reproducible data that can be used to validate computational models. Job
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large-scale facilities at the Paul Scherrer Institute, and fostering synergies with the Department of Materials (ETH Zurich). We would like to hire a Postdoctoral Researcher in the field of 3D
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on energy or heavy industry but could also be sector-overarching if it relates to relevant mitigation pathways such as carbon dioxide removal (CDR). An integral part of your work consists of advising PhD and
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Experience in handling large datasets and proficiency in programming languages R or Python Competence to work independently as well as to collaborate in a larger team of research assistants, PhD researchers
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are developing advanced methods for feature extraction, data integration, and clustering from this growing body of clinical data. We will extract and analyze a large amount of information from longitudinal multi