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) at the Karolinska Institute, Sweden. The position is funded by the European Commission through the MSCA Doctoral Network Endotrain (Grant No: 101227148) and coordinated by the University of Bergen, Norway
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responsibilities (dependent on experience level of applicant) Develop and improve multi-temporal InSAR processing algorithms (e.g., time series analysis, phase unwrapping, noise mitigation, filtering, atmospheric
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techniques to identify the enzymes, as well as protein purification and recombinant protein expression to get hold of the enzymes. The PhD student will be part of the large and international PEP group (https
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Digital. The research focuses on advanced signal analysis and machine learning methods that enable robust operation and service continuity in future wireless networks under challenging radio conditions. As
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to conduct safe experiments. Experience with optical measurement techniques. Good programming and data analysis skills (e.g., Python, MATLAB, LabVIEW). You must meet the requirements for admission
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analysis (FEA) and strong skills in FEA software such as ABAQUS Hands-on experience in the construction and application of deep learning neural networks on material design by using PyTorch or Matlab PLEASE
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are particularly suitable for a PhD education. You must meet the requirements for admission to the doctoral program from the Faculty of Engineering (https://www.ntnu.edu/studies/phiv ) You must be
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are particularly suitable for a PhD education. You must meet the requirements for admission to the doctoral program from the Faculty of Engineering (https://www.ntnu.edu/studies/phiv ) You must be
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. Familiarity with accident databases, modelling of complex systems, or network analysis. Experience with scientific writing and conference dissemination. Personal characteristics To complete a doctoral degree
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leading to a PhD degree in Cybersecurity Conduct high-quality research within the HAT-CI framework, primarily focusing on: Leading analysis and mapping of how human-AI teaming can enhance cyber defense