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to the development of several innovative doping methods. More broadly, the research aims to understand and control how molecular interactions, ions, and charge transfer processes determine the electronic properties
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acquisition and clinical interpretation. The aim of this postdoctoral project is to develop and evaluate AI‑based methods that reduce operator dependence in ultrasound imaging, with a focus on clinically
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lead advanced statistical analyses integrating ecological datasets with spatiotemporal modelling frameworks. The work will contribute with evidence-based data to development of ecosystem-based
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includes the opportunity for three weeks of training in higher education teaching and learning. The purpose of the position is to develop the independence as a researcher and to create the opportunity
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to national environmental and climate goals as well as to the Sustainable Development Goals. We are situated at Campus Ultuna in Uppsala and in Skara. Read more about the department here (https://www.slu.se/en
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candidate will lead advanced statistical analyses integrating ecological datasets with spatiotemporal modelling frameworks. The work will contribute with evidence-based data to development of ecosystem-based
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leading international technical university, we play an active role in advancing the transition towards a sustainable society. At KTH, you have the opportunity to grow and develop in a creative and dynamic
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, chloroplast biology, or protease biology Ability to work independently and collaboratively in an international research environment, with a strong drive to take ownership of the project and develop their own
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University This recruitment is also connected to the Wallenberg Initiative Materials Science for Sustainability (WISE, https://wise-materials.org ). WISE, funded by the Knut and Alice Wallenberg Foundation, is
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Join us at the forefront of life science AI. We are looking for a postdoctoral researcher to develop cutting‑edge, multimodal transformer‑based deep learning methods to extract insight from genomic