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PETs: This aspect requires a significant math background as it involves exploiting various mathematical results to develop a concrete cryptographic algorithm. Although desired, background in advanced
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Based at: Business Computer Projects, Stockport The role: An exciting opportunity has become available for a graduate to work full-time on a 2-year Knowledge Transfer Partnership (KTP) to develop
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deploying suitable analysis pipelines, quality control, publishing support, visualization and rendering services, as well as maintenance of existing tools and development of new ones. Our analyses rely almost
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Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job A Postdoctoral Research Fellow position is available to work on research related to development of predictive display systems
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required. Are you passionate about mathematical systems and control theory? Do you want to develop cutting-edge control algorithms for the security and resilience of cyber-physical systems? We welcome you to
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algorithm development A background in cellular and/or wireless communications Familiarity with FPGA programming Experience with Database Design, SQL, NoSQL and/or BigData database Enjoy collaborating and
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ALMA MATER STUDIORUM - UNIVERSITA' DI BOLOGNA - - DIPARTIMENTO DI INGEGNERIA DELL'ENERGIA ELETTRICA E DELL'INFORMAZIONE | Italy | 4 days ago
joints under transients of load current and voltage; 2) the refinement of an existing comprehensive algorithm developed in Matlab environment for life and reliability modelling of HVDC cables under typical
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on an industry innovation research project where you will be part of the research team to develop a Multimodal AI for Fire Detection & Safety Systems. Key Responsibilities: Participate in and manage the research
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. Development of optimal management algorithms for such systems to provide behind-the-meter and above-the-meter services. Where to apply Website https://careers.polito.it/ Requirements Additional Information
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accurate completion. Algorithm Design: Design and implement algorithms for tensor completion, considering the unique challenges posed by sparse and multidimensional network data. This involves developing