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Description The Clinical Artificial Intelligence Lab at NYU Abu Dhabi seeks to improve patient care by developing new machine learning methodologies that tackle unique computational problems in
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the Interpretable Machine Learning Lab (https://users.cs.duke.edu/~cynthia/home.html ) for a scientific developer to work in collaboration with other researchers on machine learning tools that help humans make better
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digital technologies within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design
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research, teaching, and leadership skills. Candidates must possess excellent communication and interpersonal skills to work effectively in our team, as well as a willingness to learn new methods and
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of the project is to exploit such data to develop generative models for aptamer design. The candidate is expected to have a strong background in machine learning and statistical physics, with a real interest for
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-electron Schrödinger equation for fermions and bosons with high accuracy and on the application of these methods to problems in the physics of oxides, semiconductors and their surfaces. Machine learning
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is currently building and commissioning a network of calibrated multi-sensor observatory-class systems, and developing novel machine learning methods with the aim of collecting science-quality data
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position in statistics, machine learning, and data science. The postdoctoral researcher will be mentored by Professor Yiyuan She and will contribute to the development of innovative statistical methods and
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for a postdoctoral role and how the proposed research fits with the research area of Dr. Haeok Lee (5 pages maximum) 4. A list of three references from individuals familiar with your scholarly and
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for an academic career are encouraged to apply. For consideration, applicants need to submit a cover letter, curriculum vitae with full publication list, statement of research interests and three letters