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the era of large population size and dense genomic data such as whole-genome sequencing, new algorithms are needed to remove the bottleneck of computational load for such a development. In the frame of a
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modular, scalable, and transparent control algorithms suitable for real-time implementation across different vehicle platforms. - Contribute to theoretical developments in stochastic model predictive
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models through specific activation functions. This project will be undertaken in collaboration with Dr Hemanth Saratchandran and Prof Simon Lucey of the Australian Institute for Machine Learning, and
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. You will work under the supervision of Prof. Francisco C. Pereira, Assoc. Prof. Carlos Lima Azevedo (DTU), Dr. Biagio Ciuffo and Dr. Georgios Fontaras (JRC). You will work on research focused
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operation Quantum algorithm implementation and benchmarking About you You have a relevant Masters deegree corresponding to at least 240 higher education credits (Physics, Nanotechnology, Engineering, Computer
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Regular Job Code 9742R5 Employee Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job Required Qualifications: * Ph.D. or Masters with equivalent experience in Computational
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their validation, how effectively they generalize and extrapolate knowledge, and how might they be improved through transfer learning. You will be supervised along your efforts by Prof. Christof Devriendt
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technologies for various applications including underwater acoustic communications. Prof. Rong (total citations 4744; h-index 37) has good track record in underwater acoustic communications. The supervisors
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the development of new algorithms for processing, analysis and inversion of active and passive seismic data and the application of these algorithms to field data. Student type Future Students Faculties and centres
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. The position is hosted at the Chair for Algorithms and Complexity, headed by Prof. Susanne Albers (http://wwwalbers.in.tum.de/index.html.en). The dissertation work will involve research in the fields