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University of Texas Health Science Center San Antonio | San Antonio, Texas | United States | about 3 hours ago
to teaching and mentoring. · Collaborative approach to patient care and research with multidisciplinary teams. Visit the UT Health candidate portal https://wp.uthscsa.edu/careers/ to apply
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the following conditions: 1. Scientific Area: Industrial Engineering. 2. Funding entity: funded by the PRR - Recovery and Resilience Plan and by the NextGenerationEU, through the scheme «Agendas para a Inovação
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/annual. The AMNH offers an extensive benefits package designed to meet the needs of our dedicated and diverse community. Pay will be determined based on several factors. The hiring range for the position
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academia. Proficiency in Portuguese and English. 3. Project Objectives: The fellow’s work plan includes activities related to the execution of the project, including the application of techniques to analyze
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, a national leader in applied aging research at the IU Center for Aging Research at Regenstrief Institute, which is renowned for innovation in healthcare delivery. The position is supported by funded
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. For more details on benefits, please see: https://hr.utexas.edu/prospective/benefits and https://hr.utexas.edu/current/services/my-total-rewards . This position is eligible for a hybrid Flexible Work
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H100s). Ideal candidates will have a strong interest and proven experience in designing, understanding, or engineering large AI models or their applications. Current PLI projects involve work with
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) , “Instituto de Engenharia de Sistemas e Computadores: Investigação e Desenvolvimento em Lisboa” is a Research and Development and Innovation Organization (R&D+i) in the fields of Computer Science and Electrical
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Faculdade de Ciências Médicas|NOVA Medical School da Universidade NOVA de Lisboa. | Portugal | about 1 month ago
holding a PhD from NOVA University Lisbon are admissible, provided that the doctoral studies were not carried out at the Faculty of Medical Sciences | NOVA Medical School. Work plan The selected fellow will
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group’s research advances polymer network design to achieve high mechanical performance for the evolving demands of modern technologies. For more details, please view https://www.ntu.edu.sg/mse/research