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Research Fellow in AI for Healthcare (1 FTE) – ArcHub ICUSafeNotes-School of Computer Science 011287
breakthroughs into commercial healthcare solutions. In the ICUSafeNotes project, we are conducting research and development of multimodal machine learning models that includes ICU note summarisation and analysis
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will investigate phage-mediated horizontal gene transfer, employing approaches such as long-read high-throughput sequencing, faecal chemostat models, random transposon insertion libraries in gut bacteria
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Department: Computer Science Vacancy ID: 036943 Closing Date: 31-Aug-2025 We are seeking an experienced Earth Observation and Modelling scientist who has knowledge of, and expertise in analysing
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Postdoc Positions Country Ireland Application Deadline 5 Sep 2025 - 12:00 (Europe/Dublin) Type of Contract Temporary Job Status Full-time Hours Per Week 39 Is the job funded through the EU Research
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We are seeking an experienced Earth Observation and Modelling scientist who has knowledge of, and expertise in analysing Earth Observation data including Satellite Remote Sensing together with Soil
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). This work is part of a larger project aiming to develop novel battery thermal management systems (BTMS). The main tasks include (i) The development of an integrated model for the BMS-BTMS
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team and participate in our vibrant research community here at CSIT. Project Title: Fault-tolerant Wireless Time Sensitive Networks This project builds on our ongoing work on modelling and simulating
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leadership on the use of generative AI for developing the machine learning model, system integration and deployment, analysis and optimisation, working closely with the Principal Investigator and managing
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projects by providing initial investment, world-class teams, and state-of-the-art infrastructure. Our model empowers visionary leaders to accelerate drug development and harness AI-driven innovation
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the CFD component of the DETECT project and support other aspects of the project (management, reporting and fieldwork). The overall project aims to assess coastal vulnerability and model it using a