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-disciplinary team and lead ongoing watershed-scale modeling in U.S.EPA SWMM software. The candidate will be expected to analyze large rainfall, hydrologic, and water quality data sets, calibrate and validate
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a new research collaborator with a PhD in building technology, preferably in the field of building materials and/or building envelope performance and/or building renovation. The candidate must be
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depth in some of the following areas (not all are required): Large-scale data analysis and learning analytics methods Experimental or quasi-experimental design; validity and measurement Working with LLMs
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more efficient use of energy. Approximately 25 colleagues work at the division, including 15 PhD students. On the international level we collaborate with universities and institutes in Europe, Asia, and
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supervision where required. For more information regarding the responsibilities for this role, please refer to the Position Description at JOBS@UNSW. Skills and Experience Summary: A PhD degree in pharmacy
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an unusual combination of challenges: data are sparse and unevenly distributed, observations are uncertain, and decisions about where to survey unfold sequentially under significant time and cost constraints
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collaborators. Required Qualifications • PhD in neuroscience, physics, computer science, applied mathematics, biomedical engineering, or a related quantitative field. PhD awarded no more than four years prior
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optimization of large language models (LLMs) and related architectures for generative tasks, continuous learning, indexing or retrieval, support of retrieval augmented generation over many data points from long
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Generation, digital double, human-like avatars. Profile PhD in Computer Vision Background in CS Research experience in gen AI, deep learning Strong computational and analytical skills, as well as experience
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employees and conducts research and teaching mainly in electrical engineering and computer technology. We are located on LTH's campus in northern Lund. Within the Division of Electromagnetics and