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PhD scholarship in Biomaterials-based Approach for the Creation of Artificial Red Blood Cells - D...
disciplines, and publish in leading journals Hold a full-time, paid position for 3 years with benefits and a structured PhD training program About the research group You will join the Biomimetics, Biocarriers
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enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education . Assessment The assessment will be made by Assoc. Prof. Leticia Hosta-Rigau. We offer
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engineering. Expertise in numerical tools (Ansys, JMAG, .etc) and programming are desirable. Experience in electrical machine prototype development would be advantageous. Eligibility and Application
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have a 1st class degree (BEng or MEng/MSc) in electrical/mechanical engineering. Expertise in numerical tools (Ansys, JMAG, .etc) and programming are desirable. Experience in electrical machine
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bioinformatics. We are looking for a talented and strongly motivated PhD student to join our enthusiastic and young interdisciplinary teams of Prof. Dmitriev (Tissue Engineering and Biomaterials Group, https
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thermochemical TES. Your main supervisor will be Prof Adriano Sciacovelli and you will join the Thermal Energy Section at DTU Construct. Your work will contribute to a paradigm shift in how complex TES systems
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the following skills and qualifications (tailored to the specific project): Driven individuals who want to be a part of a world class team Some familiarity in healthcare or engineering/image based analysis
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Sintorn, Professor in digital image processing, at the Department of Information Technology and conducted alongside researchers developing computational methods with a particular focus on deep learning and
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number of teaching and research support tasks. Profile You hold a Master’s degree in physics, mathematics, computer science, biomedical engineering, or related field or you will have obtained it by
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. David Marlevi, Prof. Ulf Hedin, and Dr. Ljubica Matic to improve stroke risk prediction for patients with carotid atherosclerosis using a multidisciplinary combination of data-driven imaging