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Field
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Institute of Veterinary and Animal Sciences are offering a PhD fellowship in immunology using zebrafish as a model commencing 1 January 2027 or after agreement. The project is part of the research
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to such inhomogeneous fields. Mathematical modelling combining physical and biological aspects offers a tool to tackle this problem. In the project, a predictive model should be enhanced and validated for cellular and
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machine learning-driven digital twins for predictive combustion modeling. The research program will cover a wide range of e-fuels (H₂, NH₃, CH₃OH, DME, OME) and their applications in industrial furnaces
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Engineering, Bioinformatics, Statistics, Applied Mathematics, Physics, or a closely related STEM field. Demonstrated experience developing AI and machine learning models for biomedical applications. Job
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 2 months ago
. Preferred qualifications include experience with: Optimal Control and/or Model Predictive Control (MPC). Modeling of deformable parts. Real-time numerical optimization. LanguagesFRENCHLevelBasic
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detailed knowledge of the performance parameters that affect their application software, as it aids in making future technology choices, predicting performance and scalability, and adapting critical software
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-wide traffic prediction Design physically consistent and interpretable machine-learning methods for dynamic traffic systems Test and validate prediction models using large-scale real-world traffic data
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detection, real-time data analysis and/or predictive modelling, particularly for dynamic and safety-critical environments. Interest in AI sustainability, including resource efficiency, scalability
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and innovation. (https://liu.se/loe ) You will work within the newly established Computational Materials Science group of Assistant Professor Waldemar Kaiser, part of the Theory & Modelling unit (led by
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authenticity of visual media and provide understandable evidence for model decisions. The candidate will investigate how general-purpose pretrained visual and multimodal representations can be adapted