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Field
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. Design explanation methods that connect predictions to meaningful spatial, temporal, frequency-domain, semantic, or example-based evidence. Evaluate robustness and transfer to unseen datasets, content
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Inria, the French national research institute for the digital sciences | Talence, Aquitaine | France | about 2 months ago
the Auctus team at the Inria center of the University of Bordeaux (Talence). Thisthesis falls within the scope of the team'sscientific axis on the design and control of robotic systems. The project will
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) invites applications for a PhD position in experimental nuclear physics. The successful applicant will contribute to hardware and analysis development for the ePIC experiment at the electron-ion collider
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complementary proteomics, and metabolomics studies. The individual will participate in: Initial project planning and experimental design with investigators from Ohio State University and outside institutions
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prediction to systems that reason, plan, interact and act in the physical world. This PhD addresses efficient long-horizon task execution in Physical AI—complex tasks needing sequences of decisions, subgoals
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research and innovation centre for nanoelectronics and digital technology. The worldwide team of 6,000 scientists, engineers, and innovators from over 100 countries, is driven by a shared passion to push
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Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg | Magdeburg, Sachsen Anhalt | Germany | about 2 months ago
Systems is inviting applications for a PhD Student (f/m/d) position. Research topic: „Designing biomolecular crystallization and precipitation processes“ The position is to be filled as soon as possible
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manipulated visual content. Study representations learned by large pretrained visual or multimodal encoders, including probing, adaptation, fusion, and efficient fine-tuning strategies. Design explanation
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Experience in simulating fluid mechanics problems using, e.g., COMSOL Experience in interdisciplinary research Experience in designing and building hardware solutions, e.g. using Arduino, Raspberry Pi, 3D
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, automated design-space exploration, and cross-technology benchmarking, providing new insights into the co-design of learning algorithms, memory technologies, and neuromorphic hardware architectures for future