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author in high-ranked peer reviewed journals. The list of publications must be included in the curriculum with a clear indication of the statistical analyses used, along with the candidate’s role in
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will combine digital twins based on established process designs and process engineering fundamentals with data-driven optimisation techniques, specifically Bayesian statistics and Bayesian optimisation
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candidate will help with: Metadata acquisition and curation of the data collected Data acquisition and storage for metabolomic analysis Performing quality control on the data produced Statistical analysis and
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complete, a master’s degree in computer science, mathematics, statistics, IT, engineering, biotechnology, bioinformatics, economics, or a related field. Experience with programming in Linux environments
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develop cancer biomarkers through statistical models, including AI driven strategies, to predict highly aggressive tissue molecular signatures for mapping future GBM relapse, linking imaging features
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for the research topic described above. This paragraph should start with the words “Suitability for research topic:”. Your qualifications You have graduated at Master’s level in machine learning, statistics
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the research project leading to the Ph.D. degree. Good written and oral proficiency in English Good results in advanced courses and applied work in statistics preferably using Stata/R Desired qualifications: A
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design and data analysis. Good to advanced experience in electro-bio-physiological (EEG, Eye Tracking, biosignals) data analysis and statistics. Excellent written and oral communication skills in English
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related experience. They should be working towards a doctorate in a specialist area and have experience conducting literature reviews, along with basic skills in statistics, data analysis, and population
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The successful applicant should/must have experience in nutrition epidemiology, preferably in aging, and in statistical analyses applicants who have experience also in independent Publishing of research results