POST-DOC IN SPARSE MULTIVARIATE METHODS
Drs. Max Turgeon and Alexandre Leblanc, from the Department of Statistics at the University of Manitoba, in partnership with IOTO International Inc., seek to hire a post-doctoral fellow to work on measuring performance of Canadian and American politicians using sparse multivariate methods. Remote work is available for this position.
IOTO International Inc., a non-partisan analysis company that specializes in using artificial intelligence to gain insights from political data, collects and analyzes a variety of data on federal, state, provincial, and municipal legislators, as well as on the corresponding legislative proceedings. In this project, the intern will use different tools to understand the structure of complex high-dimensional data (including text data) and, ultimately, measure legislative performance. Theoretical, methodological and computational tools related to the analysis of high-dimensional data will be central to the work.
In particular, to tackle problems related to ranking and measuring outlyingness for complex data, approaches relying on the concept of statistical depth functions will be investigated, including the suitability of common depth functions in the context of IOTO’s data platforms. To tackle the problem of identifying structure in high-dimensional data, dimension reduction methods will be investigated as well, including different techniques related to Principal Components Analysis, and extended to handle issues associated with sparsity, robustness and missing data. By studying the structure of high-dimensional data through both lenses, this project aims at developing methodologies that provide new insights into performance.
More generally, with this project, the intern will help develop a robust and efficient computational pipeline that incorporates and integrates the above tools with IOTO’s data platforms. From a research perspective, the intern will expand their computational skills and position themselves favourably in the rapidly evolving field of high-dimensional complex data analysis and, in particular, of text mining. The fellow will also develop industry experience, communication and project management skills, and be exposed to a fast-paced start-up environment. They will also develop important applied skills by working on real-world applications.
Qualifications: Minimum requirements:
- A PhD in Statistics or a relevant field, obtained within the last five (5) years.
- Extensive experience using a programming language (e.g. R or Python) to develop and implement statistical methodologies. Experience with Python specifically is considered an asset.
- Demonstrable communication skills.
- Prior exposure (beyond the basics) to any of the following will be considered an asset: analysis of high-dimensional data, data depth, dimension reduction techniques, analysis of text data, analysis of functional data.
Remuneration: $50,000-60,000 for one (1) year.
Duration: One (1) year.
Location: Winnipeg or remotely.
please email your resume and cover letter describing your relevant experiences to firstname.lastname@example.org.
ASSISTANT PROFESSOR IN STATISTICS (Position #31381)
The Department of Statistics invites applications for a full-time tenure-track position at the Assistant Professor rank, commencing July 1, 2022, or on a date mutually agreed upon. Salary will be commensurate with experience and qualifications.
Duties will include undergraduate teaching, graduate teaching and supervision, research and service-related activities. The successful candidate will have a track record of high quality scholarly research leading to peer assessed publications; will either have, or demonstrate the potential to establish, an independent, innovative, scholarly, externally fundable research program; will have demonstrated strength in or strong potential for outstanding teaching contributions; and will exhibit evidence of the ability to work in a collaborative environment.
The Department seeks an emerging scholar with a commitment to excellence in teaching and research. Exceptional candidates at any level will also be considered. Outstanding candidates in any area of Statistics will be considered. Candidates with expertise in Computational Statistics, High-Dimensional and Complex Data Analysis, Statistical Learning, Time Series, Environmental Statistics, and Astro-Statistics would complement the Department’s existing strengths. The successful candidate will have a Ph.D. in Statistics or a related field.
To enhance our department, we particularly invite applications from those who will increase and support our diversity, including women, Indigenous peoples, persons with disabilities, racialized persons, and those committed to an inclusive environment.
The Department currently has fourteen full time tenured and tenure-track faculty members and five Instructors, and offers a full range of both undergraduate and graduate programs in Statistics. Further information about the Department can be obtained from https://sci.umanitoba.ca/statistics/.
Winnipeg (http://www.winnipeg.ca/) is the vibrant, creative capital of Manitoba, right at the geographical centre of Canada and North America. A mid-sized city of 750,000 culturally diverse people, Winnipeg offers a community with a cosmopolitan, international flair as well as a warm, welcoming spirit. A variety of arts, culture, sports, recreation and entertainment is available to satisfy every taste; and within an easy drive of the city there are lakes, beaches and pristine wilderness areas.
Applications including a curriculum vitae, a description of teaching philosophy, a summary of research interests, a three-page research plan (including short- and long-term objectives) and contact information for three references should be sent to: email@example.com (PDF files preferred). For further information, contact the Search Committee Chair at Liqun.Wang@umanitoba.ca. The closing date for receipt of applications is February 15, 2022.
The University of Manitoba is strongly committed to equity and diversity within its community and especially welcomes applications from women, racialized persons, Indigenous peoples, persons with disabilities, persons of all sexual and gender identities, and others who may contribute to the further diversification of ideas. All qualified candidates are encouraged to apply; however, Canadian citizens and permanent residents will be given priority.
If you require accommodation supports during the recruitment process, please contact UM.Accommodation@umanitoba.ca or 204-474-7195. Please note this contact information is for accommodation reasons only.
Application materials, including letters of reference, will be handled in accordance with The Freedom of Information and Protection of Privacy Act (Manitoba). Please note that curricula vitae may be provided to participating members of the search process.