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Machine Learning Integration Develop and implement machine learning algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC
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research. The methods of our investigations are also diverse and complementary, and range from theory and computer simulations to experiments in subatomic physics. The Plasma Theory group within the Division
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algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC) to accelerate design iterations Integrate ML approaches with finite
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. Within the division, the Kádár Group conducts research in the broader field of rheology and processing of soft matter. Our ongoing projects center around three main areas: Field–matter interactions
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their own research agenda within some of the department’s core themes: Digital transformation and innovation strategy – how organizations adapt their innovation processes and strategic priorities in response
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computer. The WACQT team at Chalmers currently has about 100 members (faculty, permanent research staff, postdoctoral researchers, PhD students, and undergraduate students). WACQT is committed to promoting
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This position focuses on research related to the full recycling cycle of sodium-ion batteries. The work includes developing processes for the recovery of valuable elements, carrying out
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Product Development Material Production - and in the interaction between these areas. The research focuses on the development of the industrial process, from need to finished product while creating added
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for two years with the possibility of a one-year extension. A dynamic and inspiring working environment in the coastal city of Gothenburg . Read more about Sweden’s generous parental leave, subsidized day
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(AIMLeNS) lab is a tight-knit team of computer scientists, chemists, physicists, and mathematicians working collaboratively. Our focus is on developing practical methods that blend traditional disciplines