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that enable pragmatically adequate context-dependent language use. The project uses causal intervention methods and draws on theoretical insights from research on causation in statistics, logic and philosophy
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for early-stage cancer using statistics and/or machine learning (including deep learning where appropriate). You will join a vibrant and growing research group of 12 scientists (six postdoctoral researchers
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dopamine receptors in the striatum and substantia nigra by Western blot. Statistical analysis and representation of data using Excel and GraphPad Prism softwares. Preparation of results for presentation in
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, economics, or a related field. Minimum Requirements PhD in epidemiology, veterinary medicine, public health, data science, statistics, economics, or a related field. Strong quantitative and statistical skills
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for predicting the reliability of high-temperature structural components. This involves working with various continuum damage mechanics models and statistical reliability models. The goal is to enhance engineering
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outputs, and carry out collaborative projects with colleagues in partner institutions, and research groups. The successful candidate will have completed, or be close to completing, a PhD/DPhil in a relevant
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. A starting date earlier than fall 2026 is also possible. Applicants must hold a PhD degree in Mathematics, statistics or theoretical computer science. The terms of employment are very competitive and
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, facilitating impactful multidisciplinary collaboration, scholarly advancement, and the creation of tools and public goods. Requirements Applicants must have (or expect to have at time of appointment) a PhD in
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developing foundational statistical/AI/data-driven techniques for uncertainty quantification and visualization of complex, large-scale 2D/3D scientific data. Publishing research in leading peer-reviewed
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: Experience with analyzing GPS tracks Good data-handling skills and ability to use R (compulsary) and preferably also Python and/or GIS competently Statistical/causal inference knowledge PhD degree in a related