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work. A model is to be developed to estimate the material mass breakdown for various cell designs and cell formats. The model will be validated from teardown analysis of commercial lithium-ion battery
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strategies, novel antimicrobial materials, and experimental models that bridge laboratory discoveries to clinical applications. The program emphasises interdisciplinary collaboration across orthopaedics
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around three core scientific pillars—regenerative medicine, biomaterial science, and translational research models—SHIELD supports research on therapeutic strategies, novel antimicrobial materials, and
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effort supported by the Wallenberg Initiative Materials Science for Sustainability (WISE) and Wallenberg AI, Autonomous Systems and Software Program (WASP), a WASP-WISE NEST. This interdisciplinary setting
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Materials Science for Sustainability (WISE) and Wallenberg AI, Autonomous Systems and Software Program (WASP), a WASP-WISE NEST. This interdisciplinary setting provides a unique opportunity to work at the
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models—SHIELD supports research on therapeutic strategies, novel antimicrobial materials, and experimental models that bridge laboratory discoveries to clinical applications. The program emphasises
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her/his work she/he will gain a unique skill-set at the interface between modelling and prototyping of electrode materials, including characterization of electrodes using spectroscopical and
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professional and personal development training. Through her/his work she/he will gain a unique skill-set at the interface between modelling and prototyping of electrode materials, including characterization
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applications towards materials science. Generative machine learning models have emerged as a prominent approach to AI, with impressive performance in many application domains, including materials discovery
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application! Your work assignments We are looking for one PhD student working on generative AI/machine learning, with applications towards materials science. Generative machine learning models have emerged as a