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. To apply, click the 'Apply' button, above, and select “PhD in Mechanical Engineering – Materials and Manufacturing” before uploading your documents. For informal enquiries, please contact Dr Jun Jiang
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will be funded for three years with possibility of extension and have to enroll in a PhD program at the Graduate Center for Neurosciences, Biophysics, and Molecular Biosciences ( GGNB – collaboration
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 3 days ago
. PhD students will be funded for three years with possibility of extension and have to enroll in a PhD program at the Graduate Center for Neurosciences, Biophysics, and Molecular Biosciences (GGNB
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interfacing of the sensors. The PhD candidate will work at the Integrated Devices and Systems (IDS) group within the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) at the University
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information theory. An ideal candidate would also have knowledge of quantum mechanics of complex systems. Formal hiring requirement is a master degree in physics, computer science, or an equivalent degree
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across mechanical, materials and robotics engineering; optimisation, systems and control; and sustainable chemical engineering and biotechnology. Qualifications The ideal PhD candidate for this position is
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three years is to be expected. A PhD training programme is part of the agreement and the successful candidate will be enrolled in the Graduate School of Science and Engineering. The preferred starting
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computational modelling to be used to design and re-engineer flower architecture. The RA's main focus will be on computational modelling of gene regulatory networks for predicting the mechanisms leading
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, Water Quality, Water Resources Management, Agriculture, Remote Sensing, Electronics, Artificial Intelligence, Computer Science, Civil Engineering (Structure and Geotechnique), Mechanical Engineering, and
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computational modelling to be used to design and re-engineer flower architecture. The RA's main focus will be on computational modelling of gene regulatory networks for predicting the mechanisms leading