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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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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
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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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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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, Biomedicine, or Computational Systems Biology. Experience with NGS data or single cell-sequencing analysis is required. Competence in adipose tissue biology, cell culture work or mouse physiology would be
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verification and formal verification. runtime analysis and reconfiguration of in-vehicle TSN networks. Co-supervise students. Optionally contribute to teaching. Required qualifications: Hardware design in a
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University of Denmark, DTU. DTU Nanolab houses a state-of-the-art electron microscopy center. The work carried out at DTU Nanolab spans the range of basic topographical studies to highly sophisticated analysis
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results with AI models and system simulations to create a digital twin of the PtX process for predictive optimization and scenario analysis. Funding This PhD position is generously funded through the Villum
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-cutting and bending to break the glass panels. The project will involve the establishment of a numerical model and the acquisition and analysis of data from physical measurements in the production
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. Knowledge of health care systems, healthcare access inequalities, and health disparities, preferably within a Danish context. Experience with advanced statistical data analysis. Having experience with health