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Field
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position in Energy System Modelling The Research Center for Energy Networks (Forschungsstelle Energienetze - FEN ) at ETH Zurich was founded in 2011 to address the need for independent, credible and applied
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. The position holder will have primary responsibility for conducting the analysis and material and economic modelling in collaboration with ISR colleagues and our UK and Canadian project partners. This post is
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responsibilities for this position include the development of computational models to simulate scintillator properties using time-dependent density functional theory and Monte Carlo methods, analysis and
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prepare the work for publication. You will have a PhD/DPhil in health modelling, or related subject such as health economics or public health. You will need strong data analysis skills (such as in STATA and
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document will provide information of what criteria will be assessed at each stage of the recruitment process. Please note that this is a PhD level role but candidates who have submitted their thesis and are
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scientist in the Multimodal Language Department in the area of computer vision, machine learning, and behaviour & dialogue modelling. If you have questions about the position you wish to discuss before
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receptors in yeast. Develop insect receptor data infrastructure. Coordinate data sharing and hypothesis testing with collaborators. Publish impactful scientific papers. Required Qualifications A PhD degree
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experimentalists, modelers, and data scientists Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in field of Materials Science, Chemical Engineering, Chemistry, or a related field
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limited to, integrated cancer risk prediction model, cancer subtype discovery, genomic and epi-genomic data integration, single cell RNA-Seq data analysis, non-coding RNA data analysis, and other datasets
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to Understand and Improve Veterinary Infectious Disease Models The interdisciplinary 3RTG Graduate School invites applications for PhD positions in the field of infectious disease research using animal models