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Field
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on understanding the feasibility of climate action and developing approaches for anticipating transitions. The group has a rich international network and a strong funding track record, including with an ERC Starting
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the use of X-ray techniques through a project focusing on X-ray tomography, opening up for 3D characterization of materials developed in FibRe. In particular, the objective is to through X-ray imaging study
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these may be taken into consideration. We are looking for someone with a Ph.D. in neuropharmacology, or a related discipline, strong quantitative skills, a reasonable track record, and an enthusiastic
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practical experience in cell and molecular biological studies of mitochondria, mitochondrial proteins and/or DNA-binding proteins. The candidate is expected to have a strong track record in a relevant field
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good track record of published articles in peer reviewed journals highlighting findings from your research and experimental activities Demonstrated ability to work independently and effectively Good
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expected to have a strong track record in a relevant field of research, documented by first authorships in peer-reviewed original publications of high quality. Previous experience in the fields
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of the project’s objectives, Produce high-quality research results, project reports, and scientific publications, and Contribute to teaching or other departmental duties, up to a maximum of 10% of your working time
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strong funding track record, including with an ERC Starting Grant and as part of a MISTRA network on Low-carbon Electrification in Sweden. Who we are looking for The following requirements are mandatory
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Background in magnetic material research You have a good track record of published articles in peer reviewed journals highlighting findings from your research and experimental activities Demonstrated ability
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, computer science or similar. A successful candidate should have deep and broad knowledge and experience in machine learning and related areas with a proven academic track record. Publications in leading AI/ML