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signals. -Predictive modeling: Operational knowledge of supervised machine learning, cross-validation,data partitioning, and evaluation metrics. -Best practices: Basic use of version control (Git) and
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the application of machine learning for official statistics. The subject of the thesis will be "Exploring Large Language Models for Data-to-Text Problems" and involves the study of technical methods and approaches
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, train, and validate advanced computational models and machine learning algorithms tailored to complex datasets. Collaborate with multidisciplinary teams including biologists, engineers, and clinicians
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inference [1] modeling by combining probabilistic reasoning [2] and deep learning models [3]. The objective is thus to have a model capable to reason under uncertainty. Especially, the postdoc will research
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3D embryo images (published and those generated in the Strawbridge Lab). to quantify cell numbers and lineages. A semi-automated pipeline using deep-learning-based segmentation (Cellpose-SAM), machine
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pathways, including deactivation processes. Screening and fine-tuning catalysts to enhance performance. Developing workflows and machine learning algorithms to accelerate catalyst design (optional). Group
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external partners. Topics of particular interest include the novel development and application of machine learning models--such as large language models, multi-modal foundation models, agentic AI, embodied
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Learning in a broad sense. Particular areas of interest include, but are not limited to, development and analysis of machine learning models for scientific computing, theory and algorithms for sampling
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, Taoyuan 320317, Taiwan [map ] Subject Areas: Atmospheric Sciences / Remote sensing Meteorology / Typhoon dynamics and numerical modeling Data Mining & Machine Learning / Artificial Intelligence (AI
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upcoming areas off the beaten paths. Our three main areas of research are machine learning, distributed systems, and theory of networks. Within these three areas, we are currently working on several projects