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healthcare, IIoT, computational fintech, robot-human interaction, trustworthy AI, explainable AI, large language models, quantum computing. Where to apply Website https://www.timeshighereducation.com/unijobs
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to projects using cutting-edge molecular, cellular, and spatial profiling approaches to dissect vascular and immune signaling across injury models. Key technologies and methodologies include: · Single-cell RNA
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Documented expertise in developing and training machine learning models (ideally with a focus on LLM), high-performance computing, data management, and software architecture Strong Python programming skills
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Postdoctoral Research Associate (f/m/d) for an Interdisciplinary Research Project on AI in Education
-planning and implementation of the research program using a mixed-methods approach to analyze embedded principles or "instructional biases" in general LLMs (Large Language Models) and education-specific
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., computational, mathematical, or mechanistic modeling) is essential. The candidate should demonstrate the ability to critically evaluate scientific literature, integrate experimental data into models, and
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through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Rodentia, the largest and most diverse
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hampered by uncertainties about viable business models and reward structures. Your job This postdoctoral position is part of ReGeNL , a large national inter- and transdisciplinary research programme aimed
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genome-wide CRISPR functional screening in both mouse models and clinical samples. Working closely with computational biologists and clinicians, this interdisciplinary project offers an exceptional
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, combining computational modeling, high-throughput experimentation, and advanced characterization techniques. The position offers substantial opportunities for scientific growth, international networking, and
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approach to high-frequency electromagnetic (georadar or controlled-source electromagnetic CSEM) data modelling based on full wave 3D inversion to expand our competence in the characterisation and monitoring