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Laboratory techniques for sample preparation Analysis of mass spectrometric datasets and statistical calculations Contribute to in vitro analyses Contribute to carrying out animal experiments Contribute
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ensuring accurate and efficient analysis of system behavior under various conditions. Dynamic equivalents enable faster and potentially more reliable stability assessments, which are vital for integrating
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hands-on experience in molecular cloning, cell culture systems, mouse models, and interest in liver disease biology. Experience with R or Python and the computational analysis of next-generation
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machine learning for safe and optimal control of cyber-physical systems. The projects are expected to be funded by the VILLUM INVESTIGATOR project S4OS (“Scalable analysis and synthesis of safe, secure and
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lymphocytes Basic skills in molecular biology and biochemistry (e.g. cloning, gene expression, protein identification) Analytical skills including analysis of multi-parametric flow cytometry and experience with
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large dataset analysis, improving decision-making processes for awarding grants to firms and scientists. The PhD project could aim at the following issues: Improved Funding Decisions: How can we make
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in functional genomics methods (e.g., single-cell and bulk RNA-seq, ATAC-seq and ChIP-seq) and computational data analysis is considered highly advantageous. Selected references: Jakobsen et al., 2024
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/Scientific Analysis Institute), Dr. Bernd Werse (Göethe-universität), Associate Professor Thomas F. Søgaard (AU) and Professor Andrea Tone (McGill University). Job description The PhD project specifically
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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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analysis of nanoscale materials in hard and soft matter. Since 2018, DTU Nanolab is extended to provide expertise in soft matter from small molecule complexes to biological cells. Technology for people DTU