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. We can imagine you're curious about our application procedure . It describes what you can expect during the application procedure and how we handle your personal data and internal and external
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. Additional information The lecturer appointment of 0.4 – 1.0 FTE, is initially for two years and can be extended. We offer excellent training and career development opportunities. You will collaborate closely
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period. Handle confidential information with care and professionalism. Preferablt you also have: Experience in an international or academic environment. Experience working with HR systems (such as NMBRS
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for the Job alert Previous Next Sign up Cookies We use cookies and similar technologies to process your personal data (e.g. IP address) for personalised content, ads and third-party media integrations
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). The field of Machine Learning on Graphs aims to extract knowledge from graph-structured and network data through powerful machine learning models. Designing provably powerful learning models for graphs will
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Options Model. In this way, we encourage you to keep investing in your personal and professional development. For more information, please visit Working at Utrecht University . About us A better future for
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of the Department’s workforce. You will encourage the flow of information, proactively coordinate with the Directorate’s other departments, and foster a culture of excellence, accountability and continuous improvement
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or natural sciences. More information on future Lindau Nobel Laureate meetings . Who is it for? Students, PhD candidates and post-doc researchers (up to 5 years of postdoctoral experience) - affiliated with
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Investigator (PI), Dr Marzi. Together, you will further develop and refine the PhD case studies, the research approach and the various work packages, as well as analyse data, participate in conferences and
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. In this way, we encourage you to keep investing in your personal and professional development. For more information, please visit Working at Utrecht University . About us A better future for everyone