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Field
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rich theoretical and computational environment supported by the Multimodal Language Department. Requirements Essentials PhD (completed or near completion) in Computer Science, Computer Vision, NLP
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with regression tasks and quantitative model evaluation. You have a good publication record in leading remote sensing journals and/or computer vision conferences. You can communicate clearly in English
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University of Southern California (USC) | Los Angeles, California | United States | about 2 months ago
contexts. Preferred: Background in biomedical data, healthcare, or AI for life sciences. Experience withparallel computing. Familiarity withscientific machine learning approaches(e.g., physics-informed
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(completed or near completion) in Computer Science, Computer Vision, NLP, Machine Learning, Computer Graphics/Animation, HCI, or a related field. Strong background in deep generative modelling (diffusion
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is available after six months of employment, and paid time off for bereavement, jury duty, military service, and parental leave is available after 12 months of employment. A retirement program with a
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method development and DNA library preparation for Oxford Nanopore sequencing. Large experience in bioinformatics, machine learning and high-performance computing. Furthermore, excellent written and oral
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capabilities in a wide range of areas, including applied mathematics and computer science, experimental computing systems, scalable algorithms and systems, artificial intelligence and machine learning, data
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Research Associate. The Goodwill Computer Lab researches on a variety of computer systems topics including HPC resilience, data center power management, large-scale job scheduling and performance tuning
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PhD in biology, cognitive science, or an adjacent field (e.g. biomedicine, computer sciences); A strong academic track record, including high-quality publications (quantity is less important
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metagenomics and Oxford Nanopore Technologies sequencing. Large experience in bioinformatics, machine learning and high-performance computing in relation to microbial metagenomics and analysis of horizontal gene