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of PhD students in the project Profile We are seeking highly motivated candidates with strong achievements and a proven track record. Applicants must have: A PhD in physics, chemistry, materials science
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statistical evaluation Machine learning analyses: implementation of established and new workflows Coordination of activities with Consortium partners, including presentation of results at consortium meetings
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. Supervise Bachelor’s and Master’s theses within the scope of the project. Contribute to the preparation of research proposals and technical reports. Your profile PhD in civil/structural engineering (or
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. Supervise Bachelor’s and Master’s theses within the scope of the project. Contribute to the preparation of research proposals and technical reports. Your profile PhD in civil/structural engineering (or
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. The researcher will be supervised by Prof. Colette Heald. Profile Applicants should hold an PhD degree in atmospheric science, earth science, environmental science, chemistry, physics, or a related discipline
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learning with the physics of laser–matter interaction. Your developments will be directly validated through multiple experimental runs on state-of-the-art laser processing equipment. You will work closely
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. You will perform microstructural characterization of dry coated electrodes using physical and machine learning based methods and the electrochemical assessment of the electrodes in battery cells. Your
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, particularly on measurements and searches using jet substructure and development of advanced techniques in particle tagging, including applications using machine learning, and are expected to take leading roles
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providing technical support and troubleshooting in T cell culture, molecular cloning, and viral production workflows. Profile PhD in bioengineering or related area. Strong practical background in primary T