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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
application process here. About the position The Department of Department of Mechanical and Industrial Engineering is offering an exciting PhD position within the Norwegian Maritime AI Centre , a national
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selection process, please visit our website: www.mars.uni-bremen.de We invite you to apply if you would like to co-develop the Martian Mindset with us and unlock the creative potential for innovation
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the project website: https://faircfd.eu The recruitment process will adhere to the principles of equal opportunities, transparency and non-discrimination, in line with the European Charter for Researchers, and
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without invasive surgery. Project background We develop advanced focused ultrasound technologies, adaptive closed-loop control algorithms, and ultrasound-responsive micro/nano therapeutic carriers as an
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-felix.nl , for more information about Radboud University Faculty of Science, see https://www.ru.nl/en/about-us/organisation/faculties/science/about . Diversity Code Utrecht University, HFML-FELIX and Radboud
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that networks will adapt themselves with your needs without your intervention? Join us on this research project in close collaboration with several high-tech companies to develop and demonstrate the next
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, environmental sciences or a related field; Experience in experimental plant physiology or modelling/data analysis or image processing; A result-driven collaborator with creative ideas; Excellent communication
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on genetically and optically tractable arthropod species that satisfy a number of appealing biological and technical requirements. We combine advanced microscopy and image analysis pipelines with genetic and
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Janssen, Corporate Recruiter, via email; [email protected] . Ready to apply? You can apply directly using the apply button on the vacancy page on our website which will allow us to process your
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translational imaging research program that integrates quantitative MRI, artificial intelligence, and longitudinal clinical data to improve surgical planning, outcome prediction, and disease characterization