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conditions and policy outcomes. Desired areas of expertise include: dynamic and complex systems, agent-based modeling, computer programming (familiarity with R, Python, Netlogo), statistical analysis
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communications with excellent written, oral communication and computer skills. A team player who is able to prioritize, multi-task and work collaboratively in a diverse workforce. We regret to inform that only
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design (using computer-aided software). Special Instructions A cover letter and current CV are required as part of the application. SEAS is dedicated to building a diverse and welcoming community, and we
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of Computer Science and affiliated with the Information Systems and Human–Computer Interaction (ISCHI) research group. Your immediate leader will be the unit leader of the Information Systems and Human–Computer
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programming and open software development, high-performance computing, and research studies applying hydrologic models. Preferred Qualifications: Strong interpersonal skills to facilitate effective
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work with minimal supervision. Good computer skills, including word-processing, spreadsheets, and the Internet. The chance to contribute to development of the first effective treatments for one
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/Computer Vision. The experience in diffusion models is a plus. Have a PhD degree in computer science/engineering or related disciplines. Knowledge of autonomous vehicles or cyber security will be
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | about 17 hours ago
miscategorization of subjects with potential DILI risk during regulatory review. Through this opportunity, you will cooperate in research and training activities related to computer modeling and statistical analyses
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based on performance and funding availability. Review of applications will begin immediately and continue until the position is filled. Qualifications • PhD Degree in Electrical and Computer Engineering
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and energy materials. Preference will be given to those with knowledge of computer programming, AI and/or machining learning. Applicants are invited to contact Prof. Jianguo Lin at telephone number 2766