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multimodal vision-language models for prompt-based 3D medical image segmentation Work with large-scale clinical CT datasets and scalable deep learning pipelines Validate models in close collaboration with
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apply quantitative and data-driven models to study protein interactions and their context-dependent behaviour, linking computational predictions with condition-specific biological responses. You will have
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time of appointment. Demonstrated expertise in bioinformatics, statistics, microbiome data analysis, and/or computational methods. Experience working with large population-level datasets (e.g., NHANES
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data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn't imagine the future, we invent it. If you're passionate about joining a community that challenges the curious to deliver work
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process engineering and covers a large part of the TRL ladder. This includes basic research as well as activities within demonstration and pilot-scale testing of renewable energy technologies. Co-operation
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external) is reimagining the experimental neuroscience pipeline with big data and AI at its core. A central goal of the project is to build a foundation model of the visual brain—a “digital twin” that
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on research pertinent to the project. By scaling up data, compute and model size, large language models (LLMs) have gained an impressive and ever growing array of capabilities. The next phase of development
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process engineering and covers a large part of the TRL ladder. This includes basic research as well as activities within demonstration and pilot-scale testing of renewable energy technologies. Co-operation
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3 Apr 2026 Job Information Organisation/Company University of Twente (UT) Research Field Engineering » Aerospace engineering Engineering » Mechanical engineering Researcher Profile Recognised
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3 Apr 2026 Job Information Organisation/Company Biotechnical Faculty, University of Ljubljana Department Department of Agronomy, Chair of Soil and Environmental Science Research Field History