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with large-scale data construction and empirical research • Programming skills (R, Stata, or Python) Applications should be sent by e-mail, together with significant documents, indicating the reference
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computational mesh generation. In this role, you will apply your software engineering skills to develop and validate computational results that support large-scale, physics-based simulations across a variety of
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audio, large datasets, and multimodal neural recordings (EEG, fMRI, intracranial) to develop models with a major goal of interpretability so that we may better understand the influence of complex, natural
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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systems, large multimodal foundation model training and/or finetuning, and continuous learning pipelines. Experience in multi-modality data analysis (e.g., image, video, text). Experience working in
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well as secondary data wrangling and analyses on large, cross-national datasets from dozens of countries across 4 waves on adolescent identity, school experiences, and social outcomes. This role will also entail
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implementation of novel training strategies under experimental constraints, e.g., active learning and other data-efficient approaches Conduct large-scale benchmarking and comparative evaluation of gene
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Research FieldEnvironmental science Additional Information Additional comments Reference: 2026DILIFRUA37 Programmes: HEU-101139598-C2G Commit to Green & HEU-101116435-BIG-5 You will find the bases
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The successful candidates will join the Computer Vision, Machine Intelligence and Imaging research group, led by Prof. Djamila Aouada, to conduct research in Artificial Intelligence with a primary
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. Experience with advanced light microscopy and analysing large imaging datasets as well as core molecular biology techniques (e.g., DNA and RNA manipulation) is essential. You should hold a PhD in biological