241 image-processing-and-machine-learning "UCL" Postdoctoral positions in Netherlands
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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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As a postdoctoral researcher, your primary responsibilities will be: Develop machine learning and deep learning models, with a strong focus on computer vision, for the characterisation and
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-disciplinary domain. Specific research topics to apply to bioacoustics might include: low-footprint machine learning; acoustic signal processing enhanced by ML; human-in-the-loop/active-learning methods
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machine learning; acoustic signal processing enhanced by ML; human-in-the-loop/active-learning methods; representation learning; analysing sound sequences and vocal interactions; category discovery; Perma
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project focused on developing an advanced machine learning framework for spatio-temporal datasets. The position is for 2.5 years and is partially funded by the Dutch Research Council (NWO) through
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Trustworthy Graph Machine Learning for Population Scale Networks Job description We invite applications for a postdoctoral researcher to work on fundamental techniques for trustworthy graph machine
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10 Jul 2026 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Engineering » Civil engineering Engineering » Computer engineering Researcher Profile
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Hey machine learning enthusiast with a love for physics and complex systems, will you help us develop a new generation of road traffic prediction methods? Job description Road traffic is a highly
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understudied, but common phenomenon and building bridges to the clinic. Where to apply Website https://www.academictransfer.com/en/jobs/363083/postdoc-myelin-imaging/apply/ Requirements Specific Requirements
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-photon imaging setups. Through close collaboration with Dr Min at the Amsterdam Leukodystrophy Center, you will have the opportunity to investigate myelin remodeling in clinically relevant disease models