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restraint conditions. A key goal is to develop both a sensor system and a prediction model for the short- and long-term deformation behaviour of concrete. These tools will be applied to full-scale structural
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PhD fellowship/scholarship - Intercropping of cover crops and vegetables to mitigate nitrate leac...
, including European stakeholders from horticultural industries and universities. Project description. For technical reasons, you must upload a project description. Please simply copy the project description
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collaboration within e.g. nutrition, chemistry, toxicology, microbiology, epidemiology, modelling, and technology. This is achieved through a strong academic environment of international top class with
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apply a range of single cell genomics technologies on clinical biopsies combined with bioinformatics, and a range of targeting strategies in mouse disease models. As a member of the Center of Excellence
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contact information • Certified copy of diploma (Master’s degree in a relevant field) Shortlisting may be used in the assessment process. Further information about the PhD-study can be found at the homepage
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Job Description RISC-V open source and open standards as the nucleus for new platform models help to improve overall flexibility and productivity for a wide market access. Given the challenge
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(pressure, temperature, etc.) Signal conditioning and digitization for heterogeneous sensor inputs System-level validation and interfacing with SNN-based hardware What You Will Do Design, simulate, and verify
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R Experience with single-cell RNA-sequencing, in particular analysis of data would be an advantage Experience with mouse models and possession of a FELASA B certificate would be an advantage as both
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could include: Algorithmic Transparency and Fairness in Funding Decisions Comparative Analysis of Funding Models AI-Driven Predictive Analytics for Funding Success Policy Implications and Recommendations
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algorithmic aspects of cheminformatics. The position is founded by the Challenge Programme of the Novo Nordisk Foundation: “Mathematical Modelling for Microbial Community Induced Metabolic Diseases ”, led by