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16 Apr 2026 Job Information Organisation/Company Eberhard Karls University Tübingen Department Institute of Biomedical Engineering Research Field Engineering » Biomedical engineering Neurosciences
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, the concept of a cross-university PhD programme involving non-university institutions was developed to enable the combination of different scientific and technological disciplines relevant to biomedical data
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 1 month ago
optical and quantum measurement techniques Collaborate with interdisciplinary teams to translate the developed technology into first biomedical imaging applications Your profile Master’s degree in Physics
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real patient samples Data analysis and validation for diagnostic applications This interdisciplinary project bridges materials science, nanotechnology, biomedical engineering, and translational medicine
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/content The Joint Research Academy in Biomedical Engineering and Science of Hearing and Sensory Systems (JRA) is a joint project of the University of Oldenburg, Hannover Medical School and Leibniz
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. Working across this entire pipeline provides a rare opportunity to shape a cutting edge imaging technology from its foundational concepts through to its biomedical use cases in complex biological systems
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& regeneration, and biomedical technology & implants. These research priorities reflect our major clinical strengths, producing numerous innovations in the search for novel treatment options based on chemical
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Engineering, Physiology and Therapy of Hearing “Auditory Sciences” is a structured PhD programme that is integrated in the “Joint Research Academy in Biomedical Engineering and Science of Hearing and Sensory
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degree (or equivalent) in Biomedical Engineering, Materials Science, Chemistry, or a related discipline. Hands-on experience in electrospinning (mandatory). Experience in mammalian cell culture and
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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