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between the brain signals of different subjects. The aim of this project is developing new adaptive and machine learning algorithms to successfully decode brain signals across subjects. The prospective
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/adaptive algorithms, offline and online data analysis, conducting experimental research, and online evaluation of the developed adaptive strategies with a robotic application. The prospective students can
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-world mechanical and electromechanical systems. A successful candidate is expected to demonstrate the deep expertise required to develop and apply AI algorithms that interact directly with physical
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precision medicine based on gene sequencing time series data. Large data sets come with significant computational challenges. Tremendous algorithmic progress has been made in machine learning and related
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developing novel algorithms, but also understanding, optimising and applying developed algorithms for extraction of Digital Mobility Outcomes (e.g. gait outcomes) Very good knowledge of and experience using
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? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The research program aims to develop new sensing algorithms integrated
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, understand the design and development decisions that propagate social biases, and develop theoretical and algorithmic approaches to mitigate them. Key responsibilities include developing bias detection tools
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evolution of satellite communication systems, driven by the deployment of large Low Earth Orbit (LEO) constellations and the integration of non-terrestrial networks into future 6G infrastructures, is
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candidates must thus have a strong interest in algorithmic development as well as embedded hardware integration. Role and responsibilities This PhD project will be executed in close cooperation with
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evolution across different genomic regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods and statistical analysis (https://cgrlab.github.io