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statistical models (for example principal component analysis) to obtain insights into relationships between physical properties of polysaccharides (composition, molecular weight charge, chain length etcetera
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engineering, and hyperparameter tuning to produce resilient and high-performing models. · PhD in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field Strong track record
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” (funded by the German Research Foundation, DFG). PhD Researcher in Computational Linguistics (m/f/d, E13 TV-L, 75%) The position begins on 01 October 2025 and ends on 30 June 2029. The position is
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Forschungsgemeinschaft and the consortium SynThera funded by the Carl Zeiss Foundation (www.synthera.eu/ ). We are seeking two excellent and enthusiastic PhD students with a strong interest in microbiome research
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economic studies funded by the UK National Institute for Health and Care Research. Experience of conducting economic evaluations using suitable statistical software (e.g. STATA, R or SAS) is essential
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responsibilities of the job - Access and analyse national cancer registration data, population statistics, and mortality data by ethnicity. - Calculate ethnicity-specific absolute risk thresholds and estimate
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Parkinson’s Disease, or markers of brain structure and functioning, depending on the dataset. To do this, knowledge or willingness to be trained in advanced statistical modelling, ideally with an interest in
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Minimum Qualifications Candidates must have a PhD and proven research experience in computation analyses, statistics, mathematical modeling, or engineering. Prior experience in Ophthalmology research is not
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second PhD student focused on the development of bespoke probabilistic models. Thus, an affinity towards statistical modeling is important. In-depth skills in probabilistic modeling and hands-on experience
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the decision analytic modelling field research field and contribute to high quality reports for funding bodies and peer-reviewed outputs. You will hold a DPhil/PhD in health economics or a related quantitative