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, the Engineer will architect, engineer, and deploy AI pipelines that push technological boundaries for our clients. The Engineer will tackle complex challenges at the intersection of Large Language Models
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University Abu Dhabi, seeks to recruit a motivated Research engineer to work under the supervision of Dr. Marwa Chafii on Channel Modeling for integrated sensing and communication (ISAC). Responsibilities
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allocation from Science Faculty Niche Research Area to establish world-class research teams to develop the necessary experimental platforms, modelling and data analysis capabilities. Research Assistant
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component disciplines; in explainable multi-modal deep learning models, in causal statistical models and in human-machine teaming and AI ethics. The researcher will conduct internationally-leading research in
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environments (Slurm, job queue management), use of containers (Docker/Singularity), and reproducible analysis. - Experience in structural modelling and in silico drug discovery, including virtual screening
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. This position will direct clinically inspired research programs leveraging a large, well-annotated library of patient-derived cancer models to evaluate novel therapeutics, drug combinations and develop biomarkers
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verification and Large Language Model (LLM) safety, focusing on extending state-of-the-art logic-based automated reasoning tools such as ESBMC (https://github.com/esbmc/esbmc ) to address safety and reliability
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increasing storm intensities threaten the Belgian coast. Dunes serve as a natural safeguard, but they face significant erosion risks from wave overwash. This project aims to enhance the XBeach coastal model by
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grows rapidly and can capture substantial CO₂ in its biomass, yet typically requires very low fertilizer and pesticide inputs. Flax also fits this model: it is often grown in rotation, needs little
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available in the LEAF lab at Boise State University (https://www.leaf-ecohydrology.org/), funded by the USDA Agricultural Research Service. The successful applicant will work with a collaborative team to