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and signal processing methods using machine learning techniques to enhance the resilience, efficiency, and security of cell-free massive MIMO systems, which are expected to play a key role in next
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both sites. The project sits at the interface of cell line engineering, protein science and machine learning and you will receive advanced training in these areas while developing methods to accelerate
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learning, single-cell genomics, and neurogenetics. Your project will focus on developing new methods to understand how genetic variants affect not only individual brain cells but also change the way cells
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learning, single-cell genomics, and neurogenetics. Your project will focus on developing new methods to understand how genetic variants affect not only individual brain cells but also change the way cells
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performing data analysis of B cell receptor repertoire data using programming languages (mostly R) Successful candidates can think independently, are eager to acquire necessary new skills, and are excellent
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experience in omics data analysis, A good understanding of machine learning methods used in the single-cell data analysis, Experience or extensive studies in the analysis of single-cell transcriptomics
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integrase proteins that have a great capacity for gene transfer. Thus, the system does not depend on viral vectors for transporting the gene-editing components into the cell both ex vivo and in-vivo
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17.10.2025, Wissenschaftliches Personal Are you passionate about generative AI and digital twins for intelligent mobility systems? Do you see potential in using large language models, vision
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intrusion detection, anomaly detection, secure testbeds, and mobile app development for healthcare security monitoring. The lab collaborates with faculty, graduate students, and external partners across USNH
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targeting of host cell interactions in alphaviruses. Viruses with RNA genomes cause most of the emerging and re-emerging infectious disease epidemics. Alphaviruses are mosquito-borne viruses causing febrile