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for safeguarding financial stability and international security. This project investigates how blockchain analytics and data engineering can enhance the detection of illicit activities across these decentralised and
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Research Project“ Transforming Cardiac Research: Visual Exploration and AI Prediction Modeling of Real-Life, Multi-Modal Data” as a PhD-Position in machine learning. You will work alongside leading experts
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Organization (RTO) active in the fields of materials, environment and IT. By transforming scientific knowledge into technologies, smart data and tools, LIST empowers citizens in their choices, public authorities
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on causal and mechanistic studies of microbiome-mediated pathogenesis. This is achieved by bridging microbiology and big data analytics in a structured doctoral training environment. The need of microbiome
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analysis and analytical data analysis workflows, together with other team members Implementing AI-based microscopy image analysis software as python packages Developing algorithms to deploy machine learning
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of testicular tissue Validate gene expression at the protein level via IHC and Western blotting Analyze large-scale transcriptomic data (R, Python) Test allele-specific regulatory activity using luciferase
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Organization (RTO) active in the fields of materials, environment and IT. By transforming scientific knowledge into technologies, smart data and tools, LIST empowers citizens in their choices, public authorities
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and implantable sensors o Microfluidic-based electrochemical platforms o Data-driven sensor signal processing Fluent English proficiency (B2/C1 level or higher). Strong analytical, problem-solving
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As part of the German government's artificial intelligence (AI) strategy, the successful Saxon competence center ScaDS.AI Dresden/Leipzig (Center for Scalable Data Analytics and Artificial
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of the following topics: Strong emphasis on telecommunications and networks theoretical background Knowledge of 3GPP standards up to 5G at the system level Data Analytics and Management Problem solver Knowledge