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learning for real-time optimization, fault self-recovery, and production scheduling in industrial processes. Publish research results in top-tier international conferences and journals, and
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Postdoc: multi-risk adaptation pathways for river delta systems Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 36 to 40 Application deadline: 16
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fellows, and investigators in imaging methodologies. Assist in maintaining state-of-the-art imaging instrumentation and implementing new imaging technologies. Postdoc Expectations: The Postdoc will be
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machine-learned interatomic potentials, data-efficient and uncertainty-aware modeling, enhanced sampling, and statistical thermodynamics. Research will address property prediction and optimization as
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Independent Junior Research Group Leader (m/f/d, E14 TV-L, 100%) on Machine Learning Methods for Des
following fields: Computational design, analysis and optimization methods for building structures Data-driven AI methods, for example physics-informed neural networks Computer vision and geometry processing
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Job Description Are you excited by developing novel computational imaging methods that move from research into real-world use? Join our interdisciplinary team as a postdoc to develop advanced image
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data. Manage preferences for further information and to change your choices. Accept all cookies Reject optional cookies Skip to main content Research Associate / PhD Student / PostDoc (m/f/x
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PhD Position - Efficient Long-Context Large Models for Vision and Vision-Language-Action Systems ...
Helmholtz Association of German Research Centres | Karlsruhe, Baden-Württemberg | Germany | 4 days agoautonomous systems. You will investigate efficient long-context models for computer vision and VLA systems and apply it to autonomous driving. The research will combine attention optimization, token
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Job Description A postdoc position is available in the Embedded Systems Engineering (ESE) section at DTU Compute. The position is part of AEGIS, Adaptive Grid-Interactive Edge Datacenter Fleets , a