155 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions in Sweden
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arsenic, but other metals such as iron, manganese, lead and cobalt are also being investigated. At the department, you would take part in a strong and active scientific environment with other PhD students
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of living standards in the world. Virtually everyone in Stockholm can speak English and English is the only working language of the groups. Your profile To be eligible for employment as a postdoctor, a PhD or
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collaboration with the Multiscale Inorganic Materials group, both part of the Division of Energy and Materials at Chalmers . The two groups together comprise nine senior researchers and 27 PhD students and
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of organic semiconductor materials. Work assignments This project, funded by the Wallenberg Academy Fellows programme https://kaw.wallenberg.org/en/research/creating-greener-semiconductors , aims to provide a
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methods further, we are looking for a postdoc with a keen interest in biotechnology and protein biochemistry. About the position You will be part of an excellent team of several PhD students, PostDocs, and
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from the European Research Council and a DDLS Fellowship from the SciLifeLab and Wallenberg Swedish program for data-driven life science. The successful candidate will be working within the development
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their doctoral degree prior to that may also be eligible. Special reasons include absence due to illness, parental leave, appointments of trust in trade union organizations, military service, or similar
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-generation energy technologies. The research work will be conducted in close collaboration with PhD-students and researchers working with power electronic devices within the competence center for III-Nitride
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position is part of a five-year research program funded by the Wallenberg Foundation, which aims to develop and apply computational tools to understand the evolution of biodiversity (see https
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these questions, we will determine RNA structures in vivo using cutting-edge transcriptome-wide RNA structure probing techniques that together with computational models and machine learning algorithms will generate