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For information on moving to Ireland please see www.euraxess.ie Detailed Project Description This is an exciting opportunity to undertake a PhD as part of a Research Ireland funded project investigating the gender
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. The chair hosts its own computer cluster and has full access to the high-performance computing infrastructure at ZIH Dresden, one of Germany’s leading HPC centers. Dresden, the capital of the State of Saxony
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the controlled flow at tunable temperature and photopolymerization of the precursor. The practical work will be complemented by fluid mechanics computer simulations, including solutions employing machine learning
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tracking immune cells in cell culture and murine models of inflammation and cancer Conducting histological analysis for validation and correlation of imaging results Analyzing imaging data and contributing
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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. Investigate extreme continental climate states using Earth-system model simulations Link model results to proxy data, in particular from the Deep Dust core Present the results at international conferences and
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devices. The project will involve significant collaboration, sample exchange, semiconductor and device characterisation. For more information on the position please contact Prof. Phil Dale or Prof. Alex
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and statistical data analysis Excellent written and spoken English skills Experience with TMS and proficiency in relevant software (e.g., MATLAB, R, Python, or SPSS) is an advantage Key responsibilities
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to teaching activities (1-2 course hours per week or equivalent through student supervision) For further information please contact Prof. Frank Scholzen ( ) Your profile A Master's degree in Engineering (Energy
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(bio-)chemistry, physics, and engineering expertise to study molecules and cells, taking advantage of optical and single-molecule imaging, molecular probes, molecular biology, and 'large' data analysis