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mixed models, permutational methods, Bayesian analyses, machine learning algorithms, structural equation modeling). A good practical knowledge of R Personal characteristics To complete a doctoral degree
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skills and motivation to implement algorithms and test them in practice on large-scale problems. Programming Skills: You are proficient in at least one scientific programming language (such as Python
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, signal processing and/or wireless communication. Basic knowledge of and/or experience in working with reinforcement learning/other machine learning algorithms Excellent command of spoken and written
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, optimize the control algorithms and compare the results. The candidate should be able to develop software programs (patient simulator and graphical user interface using Matlab), to test and validate
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, Edge, IoT)• Scheduling and optimization algorithms• Data streams, data management and data pipelines• software engineeringExpert programmer• Java• at least one other programming languagePractical
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the European Regional Development Fund. Subject description The subject includes signal processing with emphasis on development and optimization of algorithms for processing single and multi-dimensional signals
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reference architecture for data visiting. This paradigm enables algorithms to securely access and process data within the environments where it resides, supporting federated learning for training machine
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Computational Biophysics/Chemistry (see also https://constructor.university/comp_phys ). The PhD position is focused on efficient algorithms for the simulation of non-adiabatic exciton transfer dynamics in light
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Fund. Subject description The subject includes signal processing with emphasis on development and optimization of algorithms for processing single and multi-dimensional signals that are closely related
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this PhD project, you will investigate the co-design between event-based learning algorithms and neuronal hardware units with multi-scale time constants. The algorithmic methodology will exploit recent