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you passionate about brain-inspired AI and sustainable tech? As a PhD Candidate, you will design real-time FPGA-based systems that mimic neural processes, enabling intelligent, on-chip learning for edge
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Apply now The Faculty of Science, Leiden Institute of Advanced Computer Science, is looking for a: PhD candidate for End-to-End Causal Learning (1.0 fte) Project description Causal inference is one
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directed evolution of biocatalysts predictable by machine learning. As part of the ML-GUIDE team, you will closely collaborate with researchers to identify commonalities and distinct aspects of engineering
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, business school scientists, system modeling and optimization researchers, computer scientists, legal experts and social scientists working on energy topics. Description of the PhD project The project
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Vacancies PhD position Towards measuring the effect of cognitive warfare campaigns Key takeaways The importance of influence operations in the information environment (a.k.a. information warfare) is
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strong academic record with a solid background in Machine Learning (Deep Learning, generative models, diffusion models). Knowledge in sensor data processing and radaris a plus. Good programming skills
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research area. Prior experience working with Neural Radiance Fields or Gaussian Splatting. Prospective applicants should have a strong academic record with a solid background in Machine Learning (Deep
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, making AI-driven teamwork more intuitive and effective. This PhD offers an exciting opportunity to work at the intersection of Interaction Design (IxD), Human-Computer Interaction (HCI), and Artificial
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, computational fluid mechanics, high-performance computing, and physics-informed machine learning. Affinity with physics-informed machine learning, computational VVUQ (verification, validation, and uncertainty
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that explores novel technology in the context of societal challenges such as health, sustainability, vitality, education, and the future of work. You will be part of a thriving PhD community working on a range of