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wsong83新蟲(chóng) (初入文壇)
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[交流]
美國(guó)猶他州立大學(xué)ECE學(xué)院Zhen Zhang教授招收2021年春季入學(xué)全獎(jiǎng)博士
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請(qǐng)注意： 猶他州立大學(xué)今年免去了博士入學(xué)的GRE分?jǐn)?shù)要求，只要求TOEFL成績(jī)。具體要求見(jiàn)：https://engineering.usu.edu/ece/ ... pplication-info.pdf 此外，如果有對(duì)formal verification，計(jì)算機(jī)體系結(jié)構(gòu)和計(jì)算機(jī)安全這三個(gè)方向都十分感興趣，并有較強(qiáng)學(xué)習(xí)能力的博士考生，可以嘗試聯(lián)系中國(guó)科學(xué)院信息工程研究所宋威老師，可以讀信工所的博士，猶他州立大學(xué)的Zhang老師擔(dān)任外導(dǎo)。 A PhD position is available (fully paid for 3 years with the possibility of extension) at the Electrical and Computer Engineering Department of Utah State University in the US. The expected starting date is early January, 2021. But a later starting date is possible. Abstract: Synthetic biology and nanotechnology place increasing demands on design methodologies to ensure dependable and robust operation. Consisting of noisy and unreliable components, these complex systems have large and often infinite state spaces that include extremely rare error states. Probabilistic model checking techniques have demonstrated significant potential in quantitatively analyzing such system models under extremely low probability. Unfortunately, they generally require enumerating the model's state space, which is computationally intractable or impossible. Therefore, addressing these design challenges in emerging technologies requires enhancing the applicability of probabilistic model checking. Motivated by this problem, this project investigates an automated probabilistic verification framework that integrates approximate probabilistic model checking and counterexample-guided rare-event simulation to improve the analysis accuracy and efficiency. This multi-institution collaborative project focuses on verifying infinite-state continuous-time Markov chain (CTMC) models with rare-event properties. It addresses the scalability problem by first applying property-guided and on-the-fly state truncation techniques to prune unlikely states to obtain finite state representations that are amenable to probabilistic model checking. In the case of false or indeterminate verification results, probabilistic counterexamples are generated and utilized to improve the accuracy of the state reductions. Furthermore, it mines these critical counterexamples as automated guidance to improve the quality and efficiency for rare-event probabilistic simulations. This verification framework will be integrated within existing state-of-the-art probabilistic model checking tools (e.g., the PRISM model checking tool), and benchmarked on a wide range of real-world case studies in synthetic biology and nanotechnology. ======================================== Project description: This position at Utah State University will be advancing and developing efficient model abstraction and state space truncation techniques for the infinite-state CTMC models. In particular, we are interested in investigating: - Algorithms for state space truncation and abstraction with improved accuracy for infinite-state systems - Prototype implementation of the developed algorithms in Java - Evaluation of the prototype on case studies in synthetic biology and stochastic computing circuits - Predicate abstraction techniques for CTMC models ======================================== Qualifications: Applicants must have a bachelor's degree in Electrical/Computer Engineering, Computer Science, or a related field. The successful candidate is expected to demonstrate strong background and interest in formal methods and algorithms, and preferably basic knowledge of probability and random process. SHe/He should be confident in independently developing academic software tools. Good writing and presentation skills in English are important as well. Knowledge of synthetic biology is preferred, but not required. ======================================== Salary: This is a fully paid position. The successful PhD candidate receive $1,600 per month. The pay is negotiable. The candidate is expected to work on average 20 hours per week during fall and spring semesters, and up to 40 hours per week during the summer. As a graduate student, you will receive full tuition waiver. Additionally, you will receive student insurance coverage. Depending on funding situation, tuition differential and fees may also be covered. ======================================== ECE Department at USU: The place of employment is the Electrical and Computer Engineering Department at Utah State University. The university is located in Logan, Utah, 88 miles (about 142 km) north of Salt Lake City. The mission of the Department of Electrical and Computer Engineering is to serve society through excellence in learning, discovery, and outreach. We provide undergraduate and graduate students an education in electrical and computer engineering, and we aspire to instill in them attitudes, values, and visions that will prepare them for lifetimes of continued learning and leadership in their chosen careers. Through research, the department strives to generate and disseminate new knowledge and technology for the benefit of the State of Utah, the nation, and beyond. The detailed graduate program description can be found at: https://engineering.usu.edu/ece/students/graduate/index. Graduate application information is available at: https://engineering.usu.edu/ece/ ... plication-info.pdf. ======================================== Additional Information about Logan: Logan is a valley community of about 125,000 people nestled in between the Wellsville Mountains and Bear River Range in northeastern of the state of Utah. The many ski resorts, lakes, rivers, and mountains in the region make it one of the finest outdoor recreation environments in the nation. The campus is 90 miles north of Salt Lake City. With views of a natural area reserve from campus, the pristine natural environment of the area makes Logan one of America’s most attractive and affordable university towns ( https://www.explorelogan.com/). ======================================== Contact: For questions about this position, please contact: Dr. Zhen Zhang (zhen.zhang@usu.edu) and Dr. Chris Winstead (chris.winstead@usu.edu) |
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wsong83
新蟲(chóng) (初入文壇)
- 應(yīng)助: 0 (幼兒園)
- 金幣: 92.5
- 帖子: 35
- 在線: 5.4小時(shí)
- 蟲(chóng)號(hào): 14911749
- 注冊(cè): 2019-04-19
- 性別: GG
- 專(zhuān)業(yè): 計(jì)算機(jī)體系結(jié)構(gòu)
3樓2020-12-07 22:43:50
IvinCHENG
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- 在線: 27.8小時(shí)
- 蟲(chóng)號(hào): 7651545
- 注冊(cè): 2017-12-20
- 專(zhuān)業(yè): 計(jì)算機(jī)軟件
2樓2020-12-07 20:10:46
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