14 machine-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" positions at Utrecht University
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Postdoc: Machine learning for wind flow prediction in coastal dunes Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 36 to 40 Application deadline: 6
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A better future for everyone. This ambition motivates our scientists in executing their leading research and inspiring teaching. At Utrecht University , the various disciplines collaborate intensively towards major strategic themes . Our focus is on Dynamics of Youth, Institutions for Open...
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under global change requires accurate and consistent soil information at global scale. Current global soil maps are derived using empirical machine learning that often ignores known soil processes
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closely with colleagues and students, you’ll apply mathematics to tackle societal challenges and bring new data-driven modelling, experiment, and computer-aided mathematics into education. We welcome
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against simpler machine-learning baselines; • train and evaluate ARCA on large-scale microbiome datasets, with attention to sparsity, batch effects, scalability, generalisation across studies and
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and students, you’ll apply mathematics to tackle societal challenges and bring new data-driven modelling, experiment, and computer-aided mathematics into education. We welcome applicants from all areas
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; profile root and leaf microbiomes using amplicon sequencing; analyse integrated microbiome and phenotyping datasets; contribute to machine-learning models predicting pathogen invasion success and plant
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)design; integrating multi-source datasets, including street-view imagery, GIS data, smartphone mobility data, and qualitative insights; applying and adapting state-of-the-art foundational AI and machine
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, physiology and disease development; profile root and leaf microbiomes using amplicon sequencing; analyse integrated microbiome and phenotyping datasets; contribute to machine-learning models predicting
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for reasoning, on efficient and explainable machine learning for extracting and structuring information from large datasets, and on combining the two in neuro-symbolic AI.