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Field
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. Experience working with large, complex datasets – such as scanner data or other point-of-sale data – is desired. Primary responsibilities of the fellow will include data management and analysis and preparation
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focus on established datasets, allowing the successful candidate to progress immediately. Subsequent analyses will focus on de novo data generation, including an NIH-funded study that is generating large
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training large language models Generative models for speech Detecting machine-generated data Anonymization of speech and text Multilingual representation learning CLSP is one of the world's largest academic
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for performing lab techniques such as in vitro and in vivo modeling of genetic alterations, and customized sequencing library preparation · Interpretate big genomic and biomedical data · Be
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aims to develop new foundations and technologies for reasoning and planning that leverage large language models (LLMs) and integrate them with complementary approaches, including program synthesis, and
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of Computational & Quantitative Medicine at the Beckman Research Institute. This project involves development and application of large-scale data analysis techniques from the Systems Biology field to molecular
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implicated genes act in neurons and circuits. We use large scale, unbiased, systematic approaches in collaborative multidisciplinary research teams. This postdoctoral fellowship in the Arlotta lab involves
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System for Data Quality, our research goal is to create fully automated processes for all phases of the data life cycle. We seek a Postdoctoral Fellow with expertise in Large Language Models (LLMs
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statistical models of large amounts of on-line data Assist with manuscript writing Supervise students (1 graduate student & 3-4 undergraduate students) Present research activities within the group and at
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applications (e.g., R package); genomic data processing; big data management (e.g., from EHR; Clarity; SQL; Power BI); software programming. Perform related duties based on departmental need. This job