Visiting Assistant Professor positions
The Department of Computer and Information Science (CIS) at the University of Oregon invites applications for two post-doctoral positions. The positions will involve both research (in support of one of the projects listed below) and teaching (two courses a year). Both aspects of the position will be supported by tenure-track faculty mentors. The expected outcomes include career development of the position holder as well as valuable research and education contributions to the department. These positions are anticipated as two-year appointments based on satisfactory performance. There will be opportunities for supplemental research summer support as well as the possibility of one-year extension. Employment begins September 16, 2011.
Applicants must have a Ph.D. in computer science or a closely related field, a demonstrated record of excellence in research, a strong commitment to teaching and engagement with students. The positions are limited to recent PhDs (within 3 years of graduation) who have not held tenure-track faculty positions.
The University of Oregon is an AAU research university located in Eugene and within one-hour drive of both the Pacific Ocean and the snow-capped Cascade Mountains. The CIS department offers a stimulating and friendly environment for collaborative teaching and research both within the department and with other departments on campus. The department's primary research emphases are in the areas of networking, programming languages, parallel and distributed computing, automated reasoning, human-computer interaction, and computer and network security. More information about the department, its programs, and current faculty can be found at http://www.cs.uoregon.edu.
Applications will be accepted electronically through the department's web site (only). Application information can be found at http://www.cs.uoregon.edu/Employment/. Applicants should submit their curriculum vitae, names of three references, a statement of research and teaching interests, a proposal for contributions to the identified project, and selected publications through the website. Review of applications will begin February 15, 2011 and continue until the position is filled.
The University of Oregon is an Equal Opportunity/Affirmative Action institution committed to cultural diversity and compliance with the Americans with Disabilities Act.
The University of Oregon is committed to create a more inclusive and diverse institution and seeks candidates with demonstrated potential to contribute positively to its diverse community.
The research projects for the two positions are as follows:
The candidate will be performing novel research on ensuring the security and privacy of homecare rehabilitation delivery systems and devices. A strong background in operating systems, networks, and security is required, with expertise in embedded systems (specifically kernel programming in embedded environments) and consumer device environments (e.g., Android, Google TV, Wii) being highly desirable. Experience with traffic analysis and protection mechanisms in home networking environments is also desirable, as is a familiarity with cloud computing environments.
The successful candidate will play a key role in a research team, and be involved in writing grant proposals, and teaching. This candidate will work with Drs. Jun Li, Stephen Fickas, and Kevin Butler, as well as talented and motivated graduate and undergraduate students within the department. The successful candidate will be mentored to facilitate transition to an independent research career through opportunities to publish in top-tier conferences and journals, as well as opportunities to gain leadership experience through managing a research team working in an exciting and innovative area.
The candidate in the area of machine learning and databases will be
mentored by Professors Dejing Dou and Daniel Lowd. We are especially interested in a researcher who can work on projects at the interface between statistical machine learning and data management. Projects would involve developing novel machine learning algorithms and representations and designing scalable, reliable databases and web-based computing systems. Application areas include biomedical data mining, health care informatics, social network analysis, and information extraction from the web. Collaborations with other professors specializing in high performance computing, cloud computing, and social networks are also possible.