42 web-programmer-developer-"https:"-"https:"-"https:"-"Linnaeus-University" Postdoctoral positions in Sweden
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. The postdoctoral scholar will take a leading role in the the BeeSYNC project, focusing specifically on: Computational Natural History. The researcher will develop deep learning models to predict individual bee age
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on the mechanisms underpinning the epigenetic control of the repetitive genome in stem cell models of early human development. The group was established in 2022 by Dr Christopher Douse and currently consists of seven
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generation, and explainability Evaluation methodologies for knowledge-intensive AI systems The project will be driven by real-world domain applications in materials, casting, and manufacturing, developed in
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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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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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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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opportunity to delve into advanced mathematical concepts and contribute to groundbreaking research in these areas. Our department offers a stimulating environment that promotes your development as a researcher
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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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). 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