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Field
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understanding with language-based reasoning. Process micro-facial expression data more efficiently in computer vision and vision language models. Create a language-guided representation for subtle facial motion
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with health/real grid data or machine learning is beneficial but not mandatory. We Offer One year funded of 3-year PhD position (SIF Doctoral Student Grant). Access to high-performance computing
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learning (FL), where multiple UAVs collaboratively train artificial intelligence models without sharing raw mission data. This supports privacy and efficiency, but it also creates a serious security risk: a
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motivation Testing whether the system performs equitably across cultural and language groups Training spans intervention design, trial methodology, human-computer interaction, and applied machine learning
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; profile root and leaf microbiomes using amplicon sequencing; analyse integrated microbiome and phenotyping datasets; contribute to machine-learning models predicting pathogen invasion success and plant
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will be responsible for the follow : (full details of duties available from the Job Description) Research Collaboration and engagement You will have completed a PhD in machine learning, computer science
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decision-making. Working with real-world data from Alliander, you will publish at leading machine learning venues while building tools with tangible impact on the Dutch energy sector. The Dutch energy
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metabolomics, lipidomics, proteomics and genomics, and combine these data using statistical and machine-learning approaches. Established markers such as neurofilament light chain (NfL) and GFAP will provide a
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at least one deep-learning framework (PyTorch preferred).•A solid grounding in machine learning. Experience with representation learning, generative models, foundation models or multimodal integration is a
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of mill and production operations. The scientific challenge will be to use the model and machine learning alongside live mill data (temperature, rolling loads etc) to reverse engineer the current