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- DIFFER; Published yesterday
- Delft University of Technology (TU Delft); 17 Oct ’25 published
- Delft University of Technology (TU Delft); Published yesterday
- Delft University of Technology (TU Delft); today published
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differences in learning, memory, and processing between these systems. This project develops the necessary methods to study how smart AI-models are compared to people, now and in the future, and sheds light on
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scientific coding skills in Python. You are strongly motivated to acquire advanced skills in Python and Fortran and in the use of high-performance computer systems you have affinity and preferably experience
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artificial intelligence, computer science, engineering, mathematics, physics, or a related discipline Demonstratable background in machine learning, information retrieval or natural language processing
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preferably with data analysis and machine learning (e.g., Python, AI frameworks). You have strong analytical and problem-solving skills, with the ability to translate complex clinical processes into structured
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of everyday life. This project aims to change that by developing AI-driven methods to assess wellbeing through video-based sentiment analyses. As a PhD student, you will develop and refine machine learning
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physical). Solid background in programming and experience with machine learning. Knowledge of participatory design and co-creation methodologies. Ability to learn independently and passion for research
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., high performance, functional array programming DSLs) to tackle challenging probabilistic and differentiable programming applications (e.g., experimental design, machine learning for science). We do so by
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FPGAs, CGRAs, and many Machine Learning accelerators, offer significant opportunities for improving performance and energy efficiency compared to traditional CPUs/GPUs. Yet, porting and optimizing code
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limited. To learn from past warmer climates and better understand the link between climate and extremes, we can use proxy-based climate reconstructions and climate models for past warmer climates. However
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and scalable. Design and build a technology demonstrator prototype of clinical-testing grade. Collaborate with interdisciplinary teams, including clinicians, engineers, and machine learning (ML) and