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. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education . Assessment The assessment of the applicants will be made by Prof
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manufacturing. As steel is highly recyclable its usage helps in creating a more sustainable world. For simulations of industrial processes concerning such complex materials one must typically rely on continuum
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the testing of newly devel-oped materials and the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission
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at international conferences You will work here The research is embedded within the chair Experimental Zoology , led by Prof. Florian Muijres . You will be supervised by Dr. Antoine Cribellier . Your qualities
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Support Grant of up to £5,000 Access to Disabled Student Allowance, paid sick leave and paid parental leave Supervisor: University of Warwick: Dr Arnab Palit, Prof Andy Metcalfe Eligibility: Satisfy UKRI's
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, sports, food safety, and environmental monitoring. By integrating electrochemical techniques and imaging technologies, the unit delivers cutting-edge solutions with real-world impact. Led by Prof. María
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embedded in the research programme of FEB’s Research Institute. The project will be supervised by Prof. Robert Lensink (Faculty of Economics and Business), email: b.w.lensink@rug.nl , Prof. Han Olff (Faculty
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the German Research Foundation (DFG), at the University of Tübingen. The project is led by Principal Investigators Prof. Dr. Michael Franke, Dr. Marlen Fröhlich (both Tübingen) and Prof. Dr. Manuel Bohn
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of Tübingen. The project is led by Principal Investigators Dr. Marlen Fröhlich, Prof. Dr. Michael Franke (both Tübingen) and Prof. Dr. Manuel Bohn (Lüneburg). The successful candidate will support the project
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learning and data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms