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wearable and ambient IoT sensing systems for activity and health monitoring. Implementing embedded AI models for anomaly detection and behaviour analysis. Working on digital twin and serverless IoT
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collaboration within e.g. nutrition, chemistry, toxicology, microbiology, epidemiology, modelling, and technology. This is achieved through a strong academic environment of international top class with
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allocation, start-up/shutdown sequences, and operational planning of PtX systems in response to dynamic market and process conditions. System Integration and Digital Twin Development: Combine experimental
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to the PhD project ie. processing and analysis of dietary intake data, statistical analyses (eg. linear mixed models) as well as evaluation of child growth and body composition data. Relevant publications
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R Experience with single-cell RNA-sequencing, in particular analysis of data would be an advantage Experience with mouse models and possession of a FELASA B certificate would be an advantage as both
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will be involved in exploring the models, designing, and measureing CMOS-based interface (coherently control, readout, and biasing) to quantum bits: Conduct a thorough review of recent research in
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research in the field of modern high voltage polymer electrolytic capacitors, develop models for lifetime prediction, methods to predict and test for reliability, understand physics of failures at elevated
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welcoming environment with an international atmosphere that fosters creativity, empathy, teamwork, and outstanding academic collaborations. You will also benefit from strong connections to leading companies
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Job Description RISC-V open source and open standards as the nucleus for new platform models help to improve overall flexibility and productivity for a wide market access. Given the challenge
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of computational chemistry. Applicants can have a background from cheminformatics including RDKit, machine learning applied to chemistry, and molecular modeling Our group and research- and what do we offer? Our