101 evolution "https:" "https:" "https:" "https:" "https:" "https:" "Linköping university" positions at KU LEUVEN in Belgium
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evaluation, the appointment will be extended for an additional three years (total of four years). Guidance in your research development within a diverse team of committed researchers You will have the
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language of this project is English, and the candidate should be proficient in written and spoken English (also at teaching level). Requirements are listed here: https://set.kuleuven.be/phd/applicants
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proven and successful publication track record in this field. - High intrinsic motivation and a strong scientific curiosity. - Ability to be inventive and to present novel ideas in method development, data
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, May 4, 2026, at 8:00 CET. If you are invited for an interview, we may ask you to present the results of a take‑home assignment. Where to apply Website https://www.kuleuven.be/personeel/jobsite/jobs
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meetings, and collaborate with academic or industrial partners where applicable. Disseminate research findings through academic publications and conference presentations. Contribute to the development
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application, please contact solliciteren@kuleuven.be . Where to apply Website https://www.kuleuven.be/personeel/jobsite/jobs/60637164?hl=en Requirements Research FieldJuridical sciencesEducation LevelMaster
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environment, with the utmost respect for academic freedom, commitment, critical thinking and personal development. For more information please contact Prof. dr. Tim Opgenhaffen, mail: tim.opgenhaffen
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reasoning about tree ensembles. This work will be undertaken in the context of Flanders AI Research Program (https://www.flandersairesearch.be/en ) 3) 1-2 PhD students working with Prof. Jesse Davis
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, please consult our project's website https://testament.project.uj.edu.pl . Do not hesitate to apply for all TESTAMENT's vacancies you are eligible for! Where to apply Website https://www.kuleuven.be
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Infrastructure? No Offer Description The PhD candidate will work on the development of advanced statistical and machine learning methods for time series prediction, with applications mainly in the field of traffic