48 developer-"https:"-"https:"-"https:"-"Fraunhofer-Gesellschaft" Postdoctoral positions in Sweden
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Description of the workplace The Department of Immunotechnology conducts research ranging from advanced technology development to biomedical studies. The main research areas include immuno-oncology
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–environment systems. A central component of the project is the development of next-generation process-based eco-epidemiological models that explicitly integrate environmental variability, ecological
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Associate Professor Stefania Giacomello. Examples of postdoctoral activities: Lead and develop independent research projects in line with the group’s focus Design, conduct and interpret computational analyses
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knowledge of cell and molecular biology techniques used to study cellular proliferation and invasion, including IHC, RT-qPCR, and Western blot. Experience in developing three-dimensional in vitro models and
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development post, and its purpose is to act as an initial step on a career path by providing the opportunity to to deepen and broaden your research expertise. The position also includes some pedagogical
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years to work in a multi-professional international team with automatization of radiotherapy treatment planning. Description of the project The project aims to develop methods for automated dose planning
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Subject description The postdoctoral fellow will join a project focused on developing protein-based electronic components, with the ultimate goal of enabling in-cell production of semiconductor
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on an undervalued receptor family: plexins. These receptors are involved in neuronal development, but also in shaping the cardiovascular, muskolskeletal systems and kidney. Further, plexins regulate immune responses
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will: a) conduct a systematic critique of the current political economy of agriculture, b) suggest desirable, viable, and achievable perennial alternatives to annual monocultures, and c) develop a
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). The project focuses on developing computational models for cancer risk assessment, integrating multiple types of data and risk factors. The main objective is to design and apply machine learning and deep