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PhD fellowship in Smart Environments and Analytics for Learning, Norway

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The Faculty of Information Technology, Mathematics and Electrical Engineering (http://www.ntnu.edu/ime) at the Norwegian University of Science and Technology (NTNU) has a vacancy for one PhD research fellow position in Smart Environments and Analytics for Learning at the Department of Computer and Information Science (http://www.ntnu.edu/idi).


The appointment is for a term of 4 years, with duties equivalent to 25%. This is a researcher training position aimed at providing promising researcher recruits the opportunity of academic development in the form of a doctoral degree.


The employment is conditional of the signature of the Agreement between the Research Council of Norway and NTNU.



Information about the department


Currently there are 24 professors and 14 associate professors at the department. In addition there are 16 adjunct associate professors, 15 postdoctoral researchers, approx. 70 active PhD students, and 18 technical/administrative staff. Five of the tenured scientific positions are held by women, and eight are from other countries than Norway. Research activities are organized into groups and strategic European and National projects as documented here http://www.ntnu.edu/idi/research.

 

Work description

 

The candidate will be a member of the Information Systems and Software Engineering research group and work with the “FUTURE LEARNING: Orchestrating 21st Century Learning Ecosystems using Analytics” project.

FUTURE LEARNING is a Norwegian Research Council funded project under Research and Innovation in the Educational Sector (FINNUT) program. FUTURE LEARNING aims at producing research that contributes towards the orchestration of multiple technologies to support better learning and teaching, and contributes to the growing international research literature. Our interdisciplinary and international team will carry out empirical-oriented research to develop new knowledge about how analytics allow us to better orchestrate different e-learning tools and learning practices. FUTURE LEARNING focuses: a) on an analysis of the prior empirical and theoretical knowledge to address requirements for efficient learning orchestration and b) iteratively develop, use and evaluate a framework for efficient orchestration of 21st century learning ecosystems. In particular, the proposed research seeks to explore, with both qualitative and quantitative data sources, practical and technical knowledge for improving 21st century learning ecosystems.


The PhD candidate will work on the design, implementation, evaluation, and revision of multiple technologies to support better learning and teaching.


The position requires strong English oral and writing skills as the candidate will be interacting with a team of international researcher and the job will include progress reports in English.


If the applicant’s studies are not from an English speaking country, the following tests can be used as documentation: TOEFL, IELTS and Cambridge Certificate in Advanced English (CAE) or Cambridge Certificate of Proficiency in English (CPE). Minimum scores are:


  • TOEFL: 600 (paper-based test), 92 (Internet-based test)

  • IELTS: 6.5, with no section lower than 5.5 (only Academic IELTS test accepted)

  • CAE/CPE: grade B or A


In addition, potential successful candidate will interviewed via Skype or other means.

 

Qualifications


  • A master's degree in Computer and Information Science or equivalent with very good results is required, with an average grade B or better as measured in ECTS (European Credit Transfer System) grades, or an education at the equivalent level.

  • Web development and data analysis programming skills.

  • Knowledge of learning management systems and user experience design.

  • Excellent written and oral communication skills.

 

Additional desired qualifications:

 

  • Expertise with learning analytics

  • Academic publications


The applicant must enclose a short research statement (up to 1000 words) describing his/her view of what the main research challenges are in the 21st century Smart Environments, Ecosystems and Analytics for Learning.


Emphasis will be put on personal qualities and potential as a researcher. High importance will also be attached to personal communication and cooperation skills.


Formal regulations


Appointments are made in accordance with the regulations in force regarding terms of employment for PhD candidates issued by the Ministry of Education and Research, with relevant parts of the additional guidelines for appointment as a PhD candidate at NTNU. Applicants must undertake to participate in an organized PhD programme of study during their period of employment. The person who is appointed must comply with the conditions that apply at any time to employees in the public sector. In addition, a contract will be signed regarding the period of employment, including duty work if relevant.


Applicants must be qualified for admission as PhD students at NTNU. See http://www.ntnu.edu/ime/research/phd for information about PhD studies at NTNU. Together with the application, include a description of the research work that is planned for completion during the period of the grant.


 

Salary conditions


The position is in code 1017 Stipendiat, salary grade range 50-62 in the Norwegian State salary scale, gross NOK 430 200 – 529 500 per year, depending on qualifications. A deduction of 2 % is made as a statutory contribution to the Norwegian Public Service Pension Fund.

 

General information


We can offer


  • an informal and friendly workplace with dedicated colleagues

  • academic challenges

  • attractive schemes for housing loan, insurance and pensions in the Norwegian Public Service Pension Fund


The Faculty of Information Technology, Mathematics and Electrical Engineering want to attract outstanding and creative candidates who can contribute to our ongoing research activities. We believe that diversity is important to achieve a good, inclusive working environment. We encourage all qualified candidates to apply, regardless of the gender, disability or cultural background.

The appointment is subject to the conditions in effect at any time for employees in the public sector.


As far as possible, the State workforce should reflect the diversity of the population. Goals of our personnel policy therefore include a balanced distribution in terms of age and gender as well as recruitment of people of immigrant background.


The appointment is subject to the conditions in effect at any time for employees in the public sector.


Under Section 25 of the Freedom of Information Act, information about the applicant may be made public even if the applicant has requested not to have his or her name entered on the list of applicants.


The application must contain


  • A cover letter including an explanation of how your research interests and background would fit the position.

  • Information about education and relevant experience (CV).

  • Certified copies of academic diplomas and certificates.

  • Applicants from universities outside Norway are kindly requested to send a diploma supplementor a similar document, which describes in detail the study and grading system and the rights for further studies associated with the obtained degree.

  • A short essay (up to 1000 words) describing at least one relevant project where the applicant had a major role, and how it relates to the challenges in the FUTURE LEARNING project.

  • Names and contact information of at least two references


Incomplete applications will not be taken into consideration.


The application must be sent electronically as one combined PDF file via this page (jobbnorge.no).


For further information, please contact Michail Giannakos, e-mail: michailg@idi.ntnu.no, phone +47 73590731.


For information about processing of applications, please contact Senior Executive Officer Anne Kristin Bratseth, phone +47 73 59 67 15, e-mail: anne.kristin.bratseth@ime.ntnu.no.

Further Information

Application Deadline : 10 April 2016

PhD fellowship in Smart Environments and Analytics for Learning : PDF

Contact Email:

Posted on 2016-03-23 00:47:44


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