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Field
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Department of Forest Resource Management The Department of Forest Resource Management conducts teaching and research in the areas of Forest Remote Sensing, Mathematical Statistics Applied to Forest
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subject, including: health economics, decision science, biostatistics, statistics. The candidate must have knowledge of or be willing to learn health economic evaluation. A further qualification such as an
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using such tools in combination with approximate hardware models and statistical techniques, thus exploring the design space of possible solutions. Finally, through design-space exploration targeting
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large datasets acquired under challenging conditions. This allows us to gain statistically relevant data and map out the influence of external parameters while working under relevant conditions. In situ
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work in a consortium consisting of university groups with complementary skills in fluid dynamics and statistical physics (Fluids and Flows, TU/e) and machine-learning techniques (AMLab, UvA), and
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analysis in biomedical data, in affiliation to the Artificial Intelligence Research Centre . The successful candidate will develop statistical and machine learning techniques to analyse biomedical data. High
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/dutch-courses . Requirements Specific Requirements About You: Curious Learner: You're eager to learn and explore, holding a Master's degree (MSc) in Statistics, Applied Mathematics, or a related field
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promote the doctoral student's working methods and aspects. Qualifications Requirements for the position are: MSc in bioinformatics Experience in bioinformatic analyses of multi-omic data from solid tumors
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statistical learning. It is well known that data can be highly sensitive, and that naive anonymization is not sufficient to avoid disclosure. Models and aggregates can also lead to disclosure as they can
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validating joint models for clinical prediction. Applicants should have: Obtained or working towards a 1st class degree in Mathematics (BSc/MMath) or Distinction level Masters in (Bio)Statistics, Data Science