108 machine-learning-"https:" "https:" "https:" "https:" "https:" "University of St" positions at KU LEUVEN in Belgium
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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
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. For more information please contact Prof. dr. Liesbet De Baets, mail: liesbet.debaets@kuleuven.be . Where to apply Website https://www.kuleuven.be/personeel/jobsite/jobs/60651356?hl=en Requirements Research
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required for teaching courses in Dutch. The candidate:•should have a broad background that allows them to teach in domains such as social psychology, cultural psychology, and/or intergroup relations.•should
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postdoctoral researchers at a high international level. •Aims to acquire competitive research funding from national and/or international agencies and submits effective research project proposals for this purpose
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Leuven will provide language training to enable you to take part in administrative meetings. Before teaching courses in Dutch of English, you will be given the opportunity to learn Dutch resp. English to
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@kuleuven.be or Prof. dr. Frank Verbruggen, mail: frank.verbruggen@kuleuven.be.In case of problems with the online application, please contact solliciteren@kuleuven.be . Where to apply Website https
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should be exclusively submitted through the consortium webpage https://raptor-consortium.com/recruitment/ RAPTORplus aims at adapting proton therapy treatment with multi-modality image information acquired
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with the online application, please contact solliciteren@kuleuven.be. Where to apply Website https://www.kuleuven.be/personeel/jobsite/jobs/60646298?hl=en Requirements Research FieldCriminologyEducation
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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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such as surgery, patient or staff scheduling using, e.g., multi-objective optimization or machine learning approaches and analyzing efficiency-fairness trade offs. The research will be conducted under