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(“overparameterized”) machine learning models, like probabilistic graphical models, deep neural networks, diffusion models, transformers, e.g. large language models, etc. SLT is based on the geometrical understanding
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Informatics, Health Data Science, Biostatistics, or a closely related area. Strong ML/deep learning foundation plus expertise in at least one of: multimodal learning, time-series modeling, or NLP. Demonstrated
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About the Opportunity About the Institute Do you want to be part of an exciting new Institute focused on combining human and machine intelligence into working AI solutions? We are launching a
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these plants. The post-doc is expected to build upon existing in-house tools and, where applicable, enhance them by means of AI (machine learning) and data-driven methods. These models are aimed to support
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, geospatial data, machine learning, or climate or hazard modeling is desired. Salary In compliance with NYC’s Pay Transparency Act, the annual base salary for this position is hourly rate of $30, depending
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health insurance, retirement plans, and paid time off. To access this tool and learn more about the total value of your benefits, please click on the following link: https://resources.uta.edu/hr/services
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Your Job: As part of an interdisciplinary project team with researchers from bioinformatics you will work on quantum algorithms for drug discovery. Here, the focus lies on machine learning and
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and develop complex, custom Artificial Intelligence models and applications. This role incorporates Machine Learning, Deep Learning, Computer Vision, Large Language Models, and Agentic AI technologies
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) provide vision, leadership and strategic direction on the exploitation of emerging digital technologies, such as Artificial Intelligence (AI), Machine Learning, cloud computing, Internet of Things (IoT) and
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Howard Hughes Medical Institute - Janelia Research Campus | Virginia Beach, Virginia | United States | about 2 hours ago
be part of a project at the intersection of protein engineering, evolution, and machine learning, which is part of HHMI’s AI for Science Initiative (ai.hhmi.org ). Our goal is to integrate