Faculty of Engineering - Civil Engineering
Competition No. - A104143289
Closing Date - Will remain open until filled.
This full time temporary position has an end date of one (1) year from date of hire December 1, 2020.
About CETT:
The Consortium for Engineered Trenchless Technologies (CETT) is dedicated to advancing the design and application of trenchless technology in Canada and across the globe. Located in Edmonton, Alberta, known as the "capital of trenchless technology", we have privileged access to trenchless pioneers and state-of-the-art-facilities through our industry partnerships. Under the NSERC Associate Industrial Research Chair (IRC) in Underground Trenchless Construction, members of this dynamic, interdisciplinary research team collaborate with industrial partners to address the most pressing challenges in the field today and lay the foundation for excellence in innovation and education.
Job description:
The Postdoctoral Fellow will work with graduate students on different trenchless projects, in particular, field data analysis of horizontal directional drilling projects. This position represents a unique and challenging opportunity at the interface between field and laboratory research in both theoretical and applied areas of trenchless technology.
Essential Functions:
Work with up-to-date data analysis techniques to analyze large datasets from projects in the field
Apply data mining/or machine learning methods to generate prediction models for trenchless construction methods
Collaborate with others to develop, refine, and debug code for data analysis and ensure clear documentation of all code developed
Coordinate with other research group members on key project deliverables
Develop and maintain clear, organized records of research findings and data analysis
Draft and revise manuscripts for publication in high impact journals
Keep current with regards to the latest knowledge of research trends and outcomes in relevant areas and apply these to advance assigned projects
Prepare abstracts for conferences and/or meetings and present research findings at meetings
Minimum Qualifications:
Ph.D. in Civil Engineering, Mechanical Engineering, Mining and Petroleum Engineering, Computer Science or a related discipline
Familiarity with data analysis programming languages, e.g. Python or Matlab
Knowledge of machine learning and/or data mining
Strong verbal and written communication skills and solid problem-solving skills
Ability to work as part of a team and meet project timelines
Preferred Qualifications:
Experience with machine learning and/or data mining in the field of Civil Engineering
Some knowledge of or familiarity with trenchless technology would be an asset
Application Instructions:
Applications should include a one-page cover letter (in docx or pdf format) expressing your past experience with data analysis and CV, as well as a sample paper, a sample development plan for a web-based software project and the names and contact information of three references. If you have a link to a past web-based software project you have been involved with, please provide that also.
To assist the University in complying with mandatory reporting requirements of the Immigration and Refugee Protection Act (R203(3) (e)), please include the first digit of your Canadian Social Insurance Number in your application. If you do not have a Canadian Social Insurance Number, please indicate this in your application.
Applications will be considered immediately until the position is filled.
We thank all applicants for their interest; however, only applicants selected for an interview will be contacted.
How to Apply
Note: Online applications are accepted until midnight Mountain Standard Time of the closing date.
All qualified candidates are encouraged to apply; however, Canadians and permanent residents will be given priority. If suitable Canadian citizens or permanent residents cannot be found, other individuals will be considered. The University of Alberta is committed to an equitable, diverse, and inclusive workforce. We welcome applications from all qualified persons. We encourage women; First Nations, Métis and Inuit persons; members of visible minority groups; persons with disabilities; persons of any sexual orientation or gender identity and expression; and all those who may contribute to the further diversification of ideas and the University to apply.