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work to discover cell specific isoforms and relate them to pathological signatures and genetic risk factors in ALS patient tissue. You will apply supervised and unsupervised machine learning methods
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approaches. What we ask of you Required PhD in machine learning, physics, or a related field. Established expertise in deep learning (familiarity with graph neural networks, transformers, diffusion and flow
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qualification) in AI (e.g., machine learning, natural language processing or computer vision); A strong scientific track record, documented by publications at first-tier conferences and journals (e.g., NeurIPS
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(PHM) for aerospace operations and maintenance, with strong expertise in sensor fusion, stochastic modeling, and machine learning. Your role: Design, build, and commission a laboratory test bench for
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(analysis/ geometry), applieddifferential geometry and machine learning;•Solid publication record in image analysis, scientific computing or machine learning.•Knowledge and practical experience in at least 3
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-based and machine-learning approaches), the digital twin will provide decision-makers and industry stakeholders with actionable insights about when, where, and how corrosion risk evolves. As a postdoc
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-coordinating internal scientific events and activities. What we ask of you The successful candidate will have: PhD degree in Human-Computer Interaction, Urban Sciences, Disability Studies, or related
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of you Required PhD in machine learning, physics, or a related field. Established expertise in deep learning (familiarity with graph neural networks, transformers, diffusion and flow based generative
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» Computer engineering Engineering » Electrical engineering Neurosciences » Neuroinformatics Researcher Profile Recognised Researcher (R2) Country Netherlands Application Deadline 6 Nov 2025 - 22:59 (UTC) Type
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? You hold a PhD degree in ecology or environmental science. You have proven experience with quantitative analytical methods (meta-analysis, regression modelling, machine learning). You have a solid basis