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implementing signal processing algorithms specifically tailored to analyze signals that contain interfering impulsive content, often encountered in data coming from main and pitch bearings. Machine learning
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courses on advanced semiconductor technologies Design pathfinding PDKs as learning assets Interuniversity research programs across Europe 🔬 Nano IC-related PhD topics include: Machine-learning for epitaxy
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breakdown spectroscopy (LIBS) and Raman spectroscopy) on metals and impurities • Development of a miniaturized laboratory setup for combined LIBS and Raman spectroscopy • Advanced machine learning
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analysis Background in biomedicine and digital pathology What we offer Embedding within a computational team, with extensive experience in computational biology and machine learning. Embedding within
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within a Research Infrastructure? No Offer Description Topics In the Computer Systems Lab, we aim to hire multiple PhD students on national and international research projects in the domain of software and
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or Nextflow A willingness to learn and apply machine learning approaches Offer A doctoral scholarship for a period of 1 year to start, with the possibility of renewal for a further three-year period after
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), machine learning, advanced use of LLMs. Experience with Unix-like environments and software development in the context of large (open-source) software projects is highly valuable. The applicant should be
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with large-scale data analysis, such as genomics or transcriptomics data Experience with a workflow management system such as Snakemake or Nextflow A willingness to learn and apply machine learning
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increasingly complex networks. By deploying and advancing techniques such as machine learning, graph-based network analysis, and synthetic data generation, the project tackles key challenges in anomaly detection
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principles that regulate host-pathogen interactions and feedback, using a combination of quantitative imaging, microfluidics, statistical analysis and machine learning tools. A specific focus will be put