[AISWorld] Vacancies: Postdoctoral Research Associate and PhD Fellowship (Digital Influence and Radicalisation)

[Hall, Margeret (KSRI)]

About the positions
The Applied Innovation Lab at UNO is hiring two research positions (PostDoc and PhD) aimed at applying deep learning to problems in influence and radicalization on online platforms. The position is ideally suited for recent graduates who are interested in applying their technical skills to challenging and important problems in deep learning. Successful applicants will contribute to the interdisciplinary team and implement algorithms in relevant (open source) software and programming environments (e.g., Matlab, R, Python). Interested PostDoc applicants please email to Prof. Hall at mahall at unomaha.edu<mailto:mahall at unomaha.edu>, and interested PhD candidates can review the application procedure on the website<https://www.unomaha.edu/college-of-information-science-and-technology/phd-it/doctoral-program/index.php>.
The starting date is open for discussion, though ideally we would like the successful PostDoc candidate to start as soon as possible/in the Spring semester for the PhD.

Qualifications
We are looking for creative and independent researchers with a degree in a subject relevant to the research, such as Computer Vision or Machine Learning. We are especially interested in applicants whose research interests match the field in the job description. Solid knowledge and experience of deep learning for the solution of computer vision problems is a requirement, as well as good programming skills.
As you will be working in an interdisciplinary team in international cooperation with universities, research organizations and companies, we expect a pro-active and collaborative attitude and excellent communication skills both in presentations and writing. Ideally, an applicant has relevant research exposure in computer vision, deep learning or machine learning, and have solid programming ability. We expect PostDoc applicants to have strong research ability demonstrated from publications in relevant fields. The applicants must be highly motivated and self-driven, eager to learn new tools and new methodologies. Knowledge and expertise in deep learning and computer vision is preferred.


About the University of Nebraska at Omaha
Located in one of America’s best cities to live, work and learn, the University of Nebraska at Omaha (UNO) is Nebraska’s premier metropolitan university. With more than 15,000 students enrolled in 200-plus programs of study, UNO is recognized nationally for its online education, graduate education, military friendliness and community engagement efforts. Founded in 1908, UNO has served learners of all backgrounds for more than 100 years and is dedicated to another century of excellence both in the classroom and in the community.

Affirmative Action/Equal Opportunity:
The University of Nebraska Omaha is committed to maintaining an environment for all students, faculty, staff, and visitors that is fair and responsible, an environment which is based on one’s ability and performance.
The University of Nebraska Omaha declares and affirms a policy of equal education and employment opportunities, affirmative action in employment, and non-discrimination in providing services to the public. Therefore, the University of Nebraska Omaha shall not discriminate based upon age, race, ethnicity, color, national origin, gender-identity, sex, pregnancy, disability, sexual orientation, genetic information, veteran’s status, marital status, religion, or political affiliation.
Applicants who are considered underrepresented in the STEM research field, applicants with disabilities, or applicants from disadvantaged backgrounds are encouraged to apply.

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Margeret Hall, Ph.D
Assistant Professor
School of Interdisciplinary Informatics
College of Information Science & Technology
The Peter Kiewit Institute, PKI 275C
University of Nebraska at Omaha
Omaha, NE 68182
Phone: (402) 554-2847
College: http://www.unomaha.edu/college-of-information-science-and-technology/school-of-interdisciplinary-informatics/