130 structures "https:" "https:" "https:" "https:" "Lawrence Berkeley National Laboratory Physics" positions at DAAD
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of mechanical cell activity – in this case growth/division and motility. For more information about the network and the project, please visit the central webpage ( https://cafe-bio.org/ ). Your Profile For our
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committed to the compatibility of family and career → further information at https://www.uni-regensburg.de/universitaet/jobs-und-karriere/familien-service In the case of essentially equal qualifications
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Description We invite applications for a fully funded PhD position within the DFG Priority Programme SPP2389. https://tu-dresden.de/mn/biologie/allgemeine_mikrobiologie/spp2389?set_language=en
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individually, e.g., through training and networking opportunities specifically for doctoral candidates (JuDocS): https://go.fzj.de/JuDocs FAIR REMUNERATION: Depending on your qualifications and assigned
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impact assessment using established and new methods (especially life cycle assessment, LCA) and recycling technologies is required we would also appreciate your willingness to get involved in the operation, construction
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your willingness to get involved in the operation, construction, and conversion of test facilities We offer: You will join a team of enthusiastic scientists who pursue creatively their individual
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courses or doctoral candidates Selection Selection is made by the National Science and Technology Council - NSTC Further information National Science and Technology Council - NSTC https://www.nstc.gov.tw
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the development of buffer structures) and AlGaN growth for AlGaN/GaN heterostructures. Exchange and collaboration with a diverse team of scientists from the REC² Cluster, in particular with those from the fields
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/ Argentina https://www.argentina.gob.ar/educacion/campusargentinaglobal Alearg E (pasantías): Estudiantes de Ingeniería
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applies), preferably via the TUD SecureMail Portal https://securemail.tu-dresden.de by sending it as a single pdf file to mlcv at tu-dresden.de or to: TU Dresden, Chair of Machine Learning