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science/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning
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of one of the two annual PhD selection processes may begin doctoral work at any time during the following six months (usually 1 September of the same year and 1 March of the following year). The duration
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processing, algorithm design, optimisation and simulation, software engineering and automation and control systems. An overview of the current PhD research projects is given here: https://www.dashh.org
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dynamic, interdisciplinary team that combines science, sustainability, and technology to create a better future. Help shape the next generation of sustainable materials inspired by nature's most powerful
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imaging. Your Profile: The successful applicant must have the following: • Master’s degree in physics, biophysics, biomedical engineering, computer engineering or electrical engineering. • Excellent track
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Your Job: At the Electrocatalysis department of Prof. Karl Mayrhofer, we offer a PhD position within the team Nanoanalysis of Electrochemical Processes. Lead by Dr. Andreas Hutzler, the team is
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/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages
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biomedical engineering, bioinformatics, biotechnology, molecular imaging and biomaterials. Training within the RegSci PhD programme takes place across three levels: students carry out their own research
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programmes. HBRS currently comprises six international PhD programmes – Molecular Medicine (since 2000), Infection Biology and DEWIN (since 2003/2010, Cluster of Excellence RESIST), Regenerative Sciences (from
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. Methods, 2024). The approach is still in its infancy; hence we need to drive the further development of the imaging technology, labeling agents and analysis approaches at the same time. To demonstrate