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Field
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for these architectures remains a key challenge. This project will explore how reconfigurable/spatial computing devices can be integrated into large-scale heterogeneous infrastructures, which include CPUs, GPUs, DPUs, and
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skills in running large scale NLP models (e.g. BERT, GPT) for financial text analysis. The candidate shall have strong research skills of using LLM-based models for firms financial Information summary
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Large vision–language models (LVLMs) can describe driving scenes and support decisions [Li25], but they sometimes hallucinate objects, relations, or events that are not present [Liu24,Liu25]. In a
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farmers. Its research focuses on areas such as cryo-conservation of genetic material, big data analytics, breeding value estimation, phenotyping of novel traits in various species, and bioinformatics
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infectious diseases, antimicrobial resistance, medical decision making and population health metrics. Interest and experience in empirical applications of economic theory, the analysis of large health data
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modeling, or machine learning - Experience with large-scale genomic data analysis (e.g., GWAS, QTL, PRS, or multi-omics integration) Strong programming skills in R or Python; familiarity with Bayesian
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expertise in collecting and analyzing high-quality nutrition data from children and families, leveraging large datasets, and applying cutting-edge technologies, including artificial intelligence (AI) and
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until the role is filled. This role is ideal for candidates considering a future Ph.D. in accounting, finance, or related fields. Responsibilities Collect and clean large-scale datasets and conduct
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applications for a Research Assistant Professor position. We seek candidates whose research examines how increasingly agentic AI (e.g., large language models, algorithmic systems) shape users’ psychological and
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and Stata. Working with large datasets, including merging files into the data archive. Creating clear data visualizations to communicate results (including GIS maps). Assisting with the preparation