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22.12.2025, Academic staff We are an interdisciplinary team at the Chair of Safety, Performance and Reliability for Learning Systems, and we are looking for exceptional PhD candidates to join our
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interaction-rich scenarios. Ideal applicants will have a strong M.Sc. in machine learning, control, or safety, and hands-on experience with robotics. Apply now: https://lnkd.in/dNjmv835. Deadline: ASAP. We
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committees. The recruiting institution will send out notification of the selection outcome after the online interview. In addition: More information can be found from the E-Sailors project web page – https
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how to find accommodation, please visit: Finding accommodation in Hamburg . For more information on how to find accommodation and how to plan your first steps in Hamburg, please see: https://www.uni
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the email server of TUD applies), preferably via the TUD SecureMail Portal https://securemail.tu-dresden.de by sending it as a single pdf file to esailors at tu-dresden.de or to: TU Dresden, Institute
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organisations within the SLICE network and in outreach activities targeted at a wide audience. A competitive salary according to MSCA regulations (see page 118ff, https://ec.europa.eu/info/funding-tenders
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within the SLICE network and in outreach activities targeted at a wide audience. A competitive salary according to MSCA regulations (see page 118ff, https://ec.europa.eu/info/funding-tenders/opportunities
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its maintenance and safety increasingly depend on data. This PhD project will develop new methods that combine remote sensing, physics-based modelling, and Bayesian machine learning to support risk
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SecureMail Portal https://securemail.tu-dresden.de by sending it as a single pdf file to esailors at tu-dresden.de or to: TU Dresden, Institute of Aerospace Engineering, Prof. Dr. Martin Tajmar
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to apply for the vacant position. Applications from severely disabled persons will be given preference if they are equally qualified ( sbv.desy.de ). You can find further information here: https