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information about us, please visit: the Department of Biochemistry and Biophysics . About the DDLS PhD student program Data-driven life science (DDLS) uses data, computational methods and artificial
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of forests in climate change are now key social issues that require more knowledge. In order to both sustainably use and safeguard forest biodiversity, a coherent basic science research program is needed
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on the following criteria: Knowledge in electric power engineering, power electronics, and power system analysis Experience in modelling, simulation, and experimental work Proficiency in Swedish and English, both
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computational facilities for testing & modelling natural clays and access to data on natural slopes in Western Coast of Sweden. These state-of-the-art resources empower you to conduct cutting-edge research with
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modern programming languages are required, as well as experience in computational or mathematical modelling. Experience with the analysis of biological data is an advantage. The candidate should have a
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the role of toe erosion in triggering landslides in sensitive clays. The focus will be on developing computational models that will quantify the erosion mechanisms, precursors and the time to failure
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cancer. The goal will be to find genetic prediction models to be able to predict which childhood cancer patients have a high or low risk of toxicity in childhood cancer. Preliminary the doctoral project
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CST Microwave Studio, HFSS or EM Pro for antenna modeling and design is required, as is experience with programming languages like MATLAB, Python, or similar for antenna array analysis and algorithm
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, or relevant fields. Excellent programming skills in modern programming languages are required, as well as experience in computational or mathematical modelling. Experience with the analysis of biological data
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social issues that require more knowledge. In order to both sustainably use and safeguard forest biodiversity, a coherent basic science research program is needed that addresses large and complex issues