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Field
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There exists an inherent variability in how lithium-ion batteries fail – an event commonly referred to as “thermal runway”. This uncertainty drives additional cost and complexity into the design and
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either (computational) Bayesian methods, or statistical learning for complex data, unsupervised learning, or matrix factorization, is an advantage. Experience with management and analysis of large datasets
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an advantage but is not a pre-requisite. • You will conduct polymer synthesis and characterization in dispersed medium and in solution, handle complex instruments, perform detailed data refinement and
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bottom up, whether it's code or biological structures. Requirements: A Master’s degree in Computational Science, Biomedical Engineering, Biophysics, Physics, Applied Mathematics, or a related field; Strong
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
, computer vision, and data analysis using industry-standard tools such as Python, MATLAB, and deep learning frameworks. The student will enhance their ability to manage complex, interdisciplinary research
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northern Sweden create enormous opportunities and complex challenges. For Umeå University, conducting research about – and in the middle of – a society in transition is key. We also take pride in delivering
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to gain insights into complex systems and inform decision-making Design and evaluate scenarios that focus on energy systems and structural change, assessing their potential impact Develop and evaluate
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related field, and a strong interest in biomedical applications. Experience in machine learning, statistics, or high-dimensional biological data analysis is advantageous. Ideal candidates are curious
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 3 months ago
5 Feb 2026 Job Information Organisation/Company Inria, the French national research institute for the digital sciences Research Field Computer science Mathematics Researcher Profile First Stage
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research ideas, and to have solid mathematical foundations, such as in linear algebra and relational algebra, to support the design and analysis of your algorithms. You should be curious, motivated, able