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in data integration, model design, and large-scale training by combining multi-modal scientific data, knowledge graphs, physics-aware machine learning, and GPU/HPC computing to develop transparent and
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(“overparameterized”) machine learning models, like probabilistic graphical models, deep neural networks, diffusion models, transformers, e.g. large language models, etc. SLT is based on the geometrical understanding
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teaching and student supervision activities in areas related to your expertise. What we ask of you Your experience and profile A PhD degree in AI (e.g., machine learning, natural language processing
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27 Feb 2026 Job Information Organisation/Company Leiden University Research Field Juridical sciences » Health law Juridical sciences » Social law Researcher Profile Recognised Researcher (R2
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at interdisciplinary conferences alongside a team of psychologists, historians, and computer scientists. What do you have to offer Must-have: You have completed a PhD in psychology, computational social science
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outcomes under different market design scenarios. The research will combine machine learning, stochastic optimization, and agent-based modelling with behavioural experiments. Case studies from emerging
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, solvent-based recycling process for complex plastic waste streams such as multilayer packaging and e-waste, while Exergy will develop the digital-twin and machine-learning tools that make the process
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competencies Education You should have completed within the past five years or be close to completing a PhD in a relevant field such as data science, AI, computer science, machine learning, Earth system science
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researchers working on hyperspectral imaging, radiative transfer modelling, machine learning, agronomy, and plant genetics. You will also work with HYDRA-EO partners in Netherlands, Spain and Italy