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seeking a highly motivated Postdoctoral Researcher to join the Machine Learning cluster. The position is part of a research project investigating how visual foundation models can efficiently acquire new
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Unity) Assist with basic data analysis, such as descriptive statistics, simple comparisons, trend identification, or visualizations Contribute to research documentation and technical writing, including
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, together with the ability to create user-centred digital solutions that are both functional and visually engaging. The ideal candidate will have experience in modern front-end technologies (such as HTML, CSS
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of findings Students may also work with analytical and clinical software such as MATLAB, Qualisys, Visual 3D, and Power BI, and contribute to literature reviews or research documentation. This position provides
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and/or case-crossover analyses, and have a promising publication record. Expertise in one or more of the following areas: statistical analysis of large data sets, machine learning, data visualization
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School graduates over a thousand students who are ready to take on great ambitions and challenges. For more details, please view: https://www.ntu.edu.sg/eee The School of Electrical and Electronic
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 1 day ago
. A complete list of Designated Countries can be found at: https://www.nasa.gov/oiir/export-control . Eligibility is currently open to: U.S. Citizens; U.S. Lawful Permanent Residents (LPR); Foreign
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(https://engineering.pitt.edu/bioengineering ) is seeking a Research Assistant Professor (Appointment Stream). Incumbent must possess a PhD in Bioengineering, Neuroscience, Neurobiology, Biomedical
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methods to enhance our suite of metabolic modeling tools, including, but not limited to, the calculation, comparison, sampling, and visualization of fluxes. He or she will use these tools to integrate and
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, acoustic, visual, and magnetic) for underwater sensing and long-range navigation for autonomous underwater vehicles. We will explore advanced non-parametric mapping techniques based on our prior work in the