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. The research will be carried out at the Department of Information and Communications Engineering, DICE, at Aalto University, Finland. The project environment offers excellent infrastructure for deep learning
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sediment management. This will be done for two case studies, namely Western Scheldt and Wadden Sea. To facilitate knowledge exchange and the learning process, interactive workshops will be organized
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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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Full-time: 35 hours per week Fixed-term: 3.5 years Help us redefine what’s possible. Be part of something bigger. Here, you can continue to make a difference in everything around you. Take on new
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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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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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Bayesian inference, likelihood-free inference, uncertainty quantification, identifiability analysis, or scientific machine learning. Strong programming skills (Python, Julia, Matlab, C++, or similar). Strong
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of engagement. Read more at: Department of Computing Science Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven
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pain and sensory processing differ between females and males, how physiological states such as pregnancy remodel neural circuits, and how maternal experiences can shape sensory function across
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to different diseases under abiotic stresses. This postdoc position offers the opportunity to learn the needs for keeping plant breeding innovative in the future, and to apply your research skills in the domain