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with expertise in materials characterisation, computer vision, computational modelling, and machine learning. The other PhD positions connected to the project are: PhD Student Position in Generative
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qualifications Marine biogeochemical processes Hydrodynamic processes related to ships, turbulence, or mixing Oceanographic modelling Data analysis and programming (e.g., MATLAB, Python, or R) Interdisciplinary
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commercial state-of-the art MMIC foundry processes and world-class measurement infrastructure allowing for a successful completion of this research project. At the Microwave Electronics laboratory currently 5
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polymers and on the development of spinning processes for manufacturing conducting polymer fibers used in wearable electronics. A summary of the research field can be found in a recent review . Project
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machine learning, computer vision, and materials science. The focus of this position is on development of neuro-symbolic models for the effective behaviour of the complex microstructure of recycled
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of on-site construction production processes, as well as sustainable development. You will also demonstrate independence, creativity, and strong collaboration and analytical skills. Research environment
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. The position is placed in the Division for Computer Networks and Systems and is formally employed by Chalmers University of Technology. Our research spans from theoretical computer science to applied systems
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. These duties can be scheduled flexibly over the year. Supportive, inclusive, and equality-focused work culture. Opportunities for national and international collaboration. Application process Your application
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, please contact: Professor Jelke Dijkstra jelke.dijkstra@chalmers.se +46 70 7722120 For questions about the recruitment process, please contact: Professor Minna Karstunen minna.karstunen@chalmers.se +46 70
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doctoral studies at Chalmers here . Application procedure The application should be written in English be attached as PDF-files, as below. Maximum size for each file is 40 MB. Please note that the system