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. Project background Misinformation has severe negative effects on personal decision-making and societal integrity. In today’s information environment, misinformation is rampant. Over the past years
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industrial partners to tackle advanced modelling, simulation, sensing, and data analysis challenges in engineering systems across sectors. Project background The COMBINE Doctoral Network aims to train a cohort
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phosphorus transport and eutrophication, using monitoring data from the EU Water Framework Directive to calibrate and validate advanced sediment routing and modelling approaches. The research will also design
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100%, Basel, fixed-term The Computational Biology (CoBi) group, led by Prof. Dagmar Iber, develops data-driven, mechanistic models of biological systems using advanced imaging and computational
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engaged in development of electrochemical sensors detecting environmental pollutants, providing real-time information for effective management. Past and current work includes electrochemical sensors
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data collectedfromtwo cattle breeds. Existing PacBio HiFi sequencing data will be complemented with ultra-long sequencing using ONT to build near complete assemblies for the sex chromosomes. This sub
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data analysis. In the Bioanalytics Group, a PhD student and a postdoctoral fellow will work together on different aspects of the microfluidic platform and sample preparation. Job description The
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at the University of Zurich, the Department of Informatics at ETHZ and several further partners, we address the challenge by the combining microfluidic technology, sequencing and fast data analysis. In
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approaches to partition existing forest flux data sets across Europe Identification of flux drivers and their temporal development to understand responses of forests to climate and extreme events Compilation
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for projects that show unconventional thinking and introduce a unique approach. The focus is on promising ideas of high originality for which preliminary data are not necessarily available (high-risk research