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an application is February 2, 2026. Project Description and Tasks In the project “All-Plant-Based Artificial Lighting Solution for Greenhouses”, we propose to design and synthesize sustainable, high- luminescent
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frameworks established around the transition labs within the national innovation program of Shift Sweden. About us The transition labs in Lindholmen and Kronoberg address how concrete design and transformation
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. The Post doc is a 2-year position. Application instructions: The application should include a well-developed research plan describing their proposed area of research within the broader scope of the project
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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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innovation in the life sciences. This creates an exciting platform with state-of-the-art infrastructure to conduct high-quality research, foster collaborations with other Swedish and international universities
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phase-matching regimes, design innovative gas targets and laser-driven generation geometries to increase XUV yield. Successful achievement of these goals promises to revolutionize XUV light generation in
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the future through education, research and innovation. As a leading international technical university, we play an active role in advancing the transition towards a sustainable society. At KTH, you have the
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travel combustion engines. The research involves computational thermodynamics (CALPHAD), high-throughput computational screening methods for alloy design, experimental alloy production (casting and/or AM
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creating inclusive environments. Flexible and Supportive: Tailored training and career development designed to balance professional growth with personal commitments. State-ot-the-art Research: Engage in
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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