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Field
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; - collaborate in the preparation of technical reports on the algorithms, mechanisms, models, or protocols developed; - develop new modules to enable the simulation and/or experimentation of emerging wireless
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AND TRAINING: - survey and analyze the state of the art in emerging wireless networks, including simulation aspects; - collaborate in the preparation of technical reports on the algorithms, mechanisms
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waveguide setups and development of PCBs for reconfigurable intelligent surfaces (RIS).; 2. Implementation, testing, and optimization of RIS control algorithms on microcontroller-based platforms.; 3
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of a multi-modal dataset.; - Implementation of a software module for storing datasets according to a pre-defined standard.; - Development of routines for testing existing ML algorithms on a multimodal
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Responsibilities: Undertake research on algorithms and data systems for next-generation data preparation and data cleaning for data analytics. Produce research papers, reports, and presentations as required by
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algorithm that reliably simulates two-phase flow. The PhD projects will be part of developing and analyzing relevant numerical methods and implement them in an open-source framework that will be made openly
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Responsibilities: Conduct research on the design and analysis of scalable machine learning systems using convex/nonconvex optimization and federated learning methods. Develop algorithms and prototypes
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algorithms, including machine unlearning techniques, to enhance model robustness and reliability. Design and execute rigorous AI testing frameworks to assess and mitigate risks in AI systems. Collaborate with
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science, with a particular focus on neuroscience applications. Designs AI techniques and algorithms for multimodal data fusion (e.g., MRI, EEG, cognitive and behavioral data, blood biomarkers, and
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computer programming to verify the efficiency of the designed solution algorithms Analyze data acquired from the field survey Develop machine learning models for prediction and recommendation Job