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using high-density EEG. Responsibilities include data collection, preprocessing, and signal analysis to investigate neural networks. By integrating these findings with neuropsychological and functional
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impact on their health. In response to this, the EU Commission, Horizon Project ‘CARAMEL’ (CArdiovascular risk Assessment via multimodal data analysis enabling prevention strategies targeting MEnopausaL
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. This employment is not offered on an indefinite basis as this project and associated activities are finite. Post status: Specific Purpose Contract This contract is a specific purpose contract for the specified
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critical component analysis, and (iii) development of Automation of ML model and data selection. The applicants should have knowledge of machine learning and optical networks and willing to engage in testbed
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biopsies, development of patient-derived organoids, metabolomics, metagenomics, advanced microscopy, dietary analysis, and classic microbiology. The project will be further supported by Public and Patient
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on an indefinite basis as this project is finite. Termination of this contract will occur on completion of the work in which you are engaged in, or in the event of the funding stream being terminated or withdrawn by
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pipelines and writing of custom MATLAB scripts for signal analysis. Prior experience in programming and statistical analysis are therefore essential. An additional component of the project will involve
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on an indefinite duration basis as this work is finite. Hours of Post: 35 hours per week Salary: Appointment will be made on the Executive Officer Salary Scale €33,191 - €51,203 per annum and in accordance with
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the university and will cease in a finite period. Termination of this contract will occur upon completion of the work in which you are engaged, or if the funding stream is terminated or withdrawn. Hours of Post
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to ensure high-quality, research-led, efficient, and transparent student learning experiences. The undergraduate teaching laboratories are vital in providing students with hands-on experience in data analysis