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Field
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activity, persistence, and safety of CAR-T cell candidates. Molecular and Cellular Biology: Employ a variety of techniques such as multicolor flow cytometry, PCR, qPCR, Western blotting, and viral and non
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will strive to continually excel as an innovative world-class university that makes a positive impact on society, living up to the University’s motto: “To learn and to apply, for the benefit of mankind
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Description In the research group Dependable and Autonomous Cyber-physical Systems (DACS) on Institute for Software and Systems Engineering (ISSE) at Clausthal University of Technology has
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across both physical and digital technologies, to deliver a cyber-physical platform for the autonomous inspection, digital representation, and maintenance of highways. The successful candidate joins a
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University explores synergies between nonlinear control theory and physics informed machine learning to provide formal guarantees on performance, safety, and robustness of robotic and learning-enabled systems
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for such applications. To respond to these challenges, this project aims to investigate automated decision making based on machine learning. The candidate (H/F) will propose and validate centralized as
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), Deep Neural Networks. Probabilistic Machine Learning and Time-series Analysis. Industrial applications of AI (energy, process industry, automation). Software development experience in teams. Programming
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the development and implementation of machine learning (ML), computer vision (CV), large language models (LLMs), and vision-language models (VLM) to automate data extraction and interpretation for productivity
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spatial omics datasets. The position will also contribute to multi-modal data integration efforts that combine imaging, genomics, and machine learning approaches. Key Responsibilities Data Processing
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machine learning for next-generation wireless networks, (ii) Foundations of semantic communications and age of information, (iii) Stochastic geometry and spatial modeling of large-scale wireless systems