22 social-network-analysis Postdoctoral research jobs at Chalmers University of Technology in Sweden
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, diversity, and gender equality, supported through networking and mentoring activities. A friendly and inclusive working atmosphere, both within the research group and across Chalmers. About the research
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Parkinson. We use in vitro biophysical analysis to characterise protein aggregates and their formation in combination with advanced live cell fluorescence imaging and cell model development to study protein
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Join a young team with a strong national and international network in the field of the rapidly expanding area of metal additive manufacturing at Chalmers University of Technology ! This postdoc
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fluids, flow-induced pattern formation in both simple and complex flows (e.g. flow instabilities, product defects), multiscale analysis, and the application of machine learning techniques. About the
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challenges and real-world impact. Project overview In recent years, generative neural network models for creation of photo-realistic images have become increasingly popular. Their training results in a low
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). This position offers a unique opportunity to collaborate closely with researchers across the Division of Marine Technology at Chalmers University, with a focus on maritime transportation risk analysis. Project
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of managing reverse logistics for returned products, and the potential disruptions to existing distribution networks. About us and the research project The division of Supply & Operations Management (SOM
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network of national and international collaborators. Project overview The aim of this two-year project is to validate and further develop advanced numerical models (originally developed at Chalmers
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biomass characterization, biomaterial characterization and application. Experience in glycomic analysis is highly recommended. Laboratory experience in biomass transformation in materials and water based
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applications, specifically targeting the prognosis and risk prediction of Heart Failure (HF) in patients. This research integrates AI safety, explainability, and multimodal medical data analysis to enhance