https://github.com/UBC-MDS/mds-stats-teaching-fellow
The University of British Columbia, Vancouver (http://www.ubc.ca/about) invites applications for a Postdoctoral Teaching & Learning Fellow, associated with a proposed Master of Data Science (MDS) program which is pending approval from the B.C. Ministry of Advanced Education. This program is a collaborative effort of theDepartment of Computer Science (https://www.cs.ubc.ca/) and theDepartment of Statistics (http://www.stat.ubc.ca/), within the Faculty of Science (http://science.ubc.ca/). The Fellow will be based in the Department of Statistics but work closely with colleagues from both departments, including another Fellow based in Computer Science.
The MDS program will focus on the innovative and responsible use of Data Science tools across a broad spectrum of data types and domain areas. It is a 10-month, full-time program, delivered in course modules of two-week and four-week durations. The last two months are devoted to a capstone project. Pending approval, the first cohort of MDS students will arrive in September 2016. Thus this position offers an opportunity to shape the delivery of the program from its inception. The Fellow will:
* Identify and develop instructional materials, including appropriate datasets, in collaboration with participating faculty.
* Be the primary instructor for a subset of the modules and provide instructional support to other faculty instructors for the remainder.
* Work with MDS Directors and faculty to expand the MDS curriculum and keep it current.
* Supervise teaching assistants.
* Foster a positive learning environment for MDS students and be the main continuous presence with the student cohort over the 10 months.
* Mentor MDS students undertaking capstone projects and liaise with project partners.
We aim to recruit a junior scholar who is committed to both the practice and the teaching of Data Science and who is drawn to an academic environment. There are also opportunities for the Fellow to contribute to other Data Science research projects undertaken by the Statistical Consulting and Research Laboratory within the Department of Statistics.
The position is subject to final budgetary approval. The Fellow will be appointed for one year, with the intent of renewal for one or more additional years. The preferred start date is as early as feasible, and must be well in advance of the anticipated arrival of the first student cohort in September 2016. The Fellow will primarily report to the MDS Academic Program Director. We anticipate being able to offer a competitive salary compared to norms for postdoctoral fellowships.
Applicants should hold a PhD in an area relevant to Data Science and have some background in Statistics. They should have experience in at least one of these areas and enthusiasm for all: practical data management and analysis; teaching at the postgraduate level; curriculum development; R/Python/SQL; version control and other practices related to collaborative and reproducible scientific work. Inquiries about qualifications or the proposed program can be directed This email address is being protected from spambots. You need JavaScript enabled to view it..
UBC hires on the basis of merit and is strongly committed to equity and diversity within its community. We especially welcome applications from visible minority group members, women, Aboriginal persons, persons with disabilities, persons of minority sexual orientations and gender identities, and others with the skills and knowledge to productively engage with diverse communities. All qualified candidates are encouraged to apply; however Canadians and permanent residents will be given priority.
Applicants should compile a single PDF file with the following elements: cover letter, curriculum vitae, contact information for three references, and any other pertinent information (e.g., evidence of teaching effectiveness or links to relevant data scientific work). The cover letter should specifically address how this position relates to the applicant’s experience and career aspirations. The file should be sent This email address is being protected from spambots. You need JavaScript enabled to view it.. Applications will be reviewed as they arrive; those received by 2016 February 12 will receive full consideration.
