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.
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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
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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.
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Salary:
This is a fully paid position. The successful PhD candidate receive
$1,600 per month. 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.
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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/files/pdfs/ece-graduate-program-application-info.pdf.
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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/).
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Contact:
For questions about this position, please contact:
Dr. Zhen Zhang (
zhen....@usu.edu) and Dr. Chris Winstead
(
chris.w...@usu.edu)