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with attention to quality, integrity, creativity, and cooperation. You are fluent in Python, machine learning, and deep-learning tools (e.g., TensorFlow, PyTorch). You can speak and write fluently in
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computer scientist who can lead a research group where the development of new machine learning techniques serves as an important basis for tackling challenging biotechnological issues. Your achievements in
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communications systems with experts in wireless communication, signal processing, digital, analog and mm-wave design, and machine learning. This is a unique opportunity to develop innovative, multi-disciplinary
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complex omics data. Therefore, knowledge of programming languages such as Python or R is necessary and prior experience with data science, high-throughput omics, Linux command line, machine learning and
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, and heterogeneity of 6G networks, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, quantum conputing, graph theory, graph-signal processing, and
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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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a strong interest in and/or experience with quantitative research methods, including psycho-physiological and behavioral measures and advanced statistical (and/or machine learning) methods. You have a
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that combines machine learning and knowledge-based inference. In real-world applications, it is often paramount to exploit expert knowledge for the task at hand. However, this poses significant challenges with
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networks, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our
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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