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related field at the level of a master degree Programming skills (Python) and experience with common machine learning platforms Experience with deep learning, computer vision, medical image analysis
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experimentation. The PhD student will develop models and algorithms for the joint design of sensing, communication, inference, and action, and is expected to contribute to a real robotic platform integrating
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PhD Scholarship in Development of Cement-Free Living Building Materials for Sustainable Construction
broad scientific network and gain hands-on experience with complementary expertise and facilities. Responsibilities and qualifications As a PhD candidate, you will take a leading scientific role in
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should have hands-on experience with microfabrication, nanofabrication or experimental device work, and be comfortable with systematic laboratory work, data analysis and troubleshooting. The project spans
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. You are highly motivated to investigate Arctic and Greenland environmental change and have a strong interest in paleoclimate and paleoceanography. Experience with one or more of the following would be
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complex with the new analogues, progressing to time-resolved SSX experiments at MicroMAX. The work will involve close collaboration with coworkers at UCPH and secondments to the University of Gothenburg
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. The candidate should have documented training and experience using social science methods (qualitative and/or quantitative). Knowledge of theory of research integrity and philosophy of science is preferable. What
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-driven modelling. Experience with numerical modelling, simulation, optimization, control, or engineering-data analysis. Good programming skills in Python, MATLAB/Simulink, or a comparable scientific
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. The position is fixed term and full-time and includes both research and teaching activities. The PhD scholarship is part of the research project Not Liking School: Lived Experience of School Emotions, funded by
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and fatigue analysis. Experience in coding (e.g., Python) and in the use of structural analysis software (e.g., Abaqus, OpenSees) is desirable. Familiarity with virtual sensing techniques, state