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assays, complemented by mass-spectrometry-driven chemical profiling and machine-learning-supported multivariate analysis. Where relevant, CRISPR-Cas-based genetic perturbations in mammalian cell models
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the production of polymer latexes that involves a complex, heterogeneous polymerization system and leads to polymers with a diverse range of structures. This project looks to use machine learning to better target
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growing and supportive team with internationally recognized expertise in data management and machine learning. The group has a strong network of national and international collaborators in both academia and
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in the 2025 QS World University Rankings by Subjects. We are hiring a Research Fellow in Signal Processing and Machine Learning to develop signal processing and machine learning algorithms and methods
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fellowship: Novel microfluidics and machine learning tools for unravelling environmental microbiomes Within the remit of the ERA Chair project REACTORS 5.0 “Sustainable REACTOR and microreactor designS
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research in Physics-Informed Machine Learning (PIML) for metal additive manufacturing process. This role will focus on developing novel machine learning frameworks that seamlessly integrate physical
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learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key Responsibilities Participate in and manage the research project together with the PI, Co-PI
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Faculty of Life Sciences - Department of Biology Research fellow (m/f/d) in the field of Machine learning and Biomedicine with expected full-time employment - E 13 TV-L HU (third-party funding limited until
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Overview of the Role Are you experienced in machine learning and looking to apply your skills to solve new challenges and reduce disaster risk? Do you want to further your career in one of the UKs
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advance research in computer vision, machine learning, and/or robotics for the digitalization, monitoring, and automation of civil infrastructure. The role will focus on developing innovative methodologies