81 learning-"https:"-"https:"-"https:"-"https:"-"https:" research jobs in Netherlands
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the intersection of machine learning (ML) and the sounds of wildlife (“bioacoustics”). We are also happy to consider candidates in one of the two fields who can demonstrate a strong basis for working in this cross
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We are seeking a postdoctoral researcher with a curiosity-driven record who works at the intersection of machine learning (ML) and the sounds of wildlife (“bioacoustics”). We are also happy
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Hey machine learning enthusiast with a love for physics and
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» Learning studies Educational sciences » Teaching methods Researcher Profile Recognised Researcher (R2) Application Deadline 17 Aug 2026 - 21:59 (UTC) Country Netherlands Type of Contract Temporary Job Status
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interactions between individual cells. Where to apply Website https://www.academictransfer.com/en/jobs/362788/post-doc-learning-interactions-… Requirements Specific Requirements PhD Degree in Physics Preferably
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design, train and implement ARCA: an AI foundation model for crop microbiomes. You will work at the interface of deep learning, bioinformatics and microbial ecology, using large-scale microbiome and genome
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verbal and written, and in English at language level C1 and preferably also in Dutch. If you don’t speak Dutch yet, we expect the willingness to learn Dutch. Of course we will support you in that.
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The Faculty of Behavioural and Social Sciences (GMW) excels in research and teaching in the areas of behaviour, thinking, learning, and participation in society. More than 4,500 students and
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, Computational Cognitive Science, Intelligent Systems, Culture Studies, Philosophy, and the Tilburg Center of the Learning Sciences. Collaboration across disciplines is encouraged among both researchers and
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-source scientific software library. You will be part of a larger project at the Uncertainty in Complex Systems lab (PI: Dr Max Hinne) aimed at learning which statistical and/or computational model is most