National Postdoctoral Fellowship Program
Distinguished Postdoctoral Fellowships
This program provides a comprehensive training experience to prepare postdoctoral fellows for success in a variety of careers.
Support Amount: up to $70,000 per year plus benefits
- Faculty Proposals due Oct 14, 2022
- Postdoctoral Fellow Recruitment takes place Oct 15, 2022 – Jan 15, 2023
Program Duration: 2 years
Eligibility: Faculty & Doctoral Graduates
Have questions about the program?
The overarching goal of the CANSSI National Postdoctoral Program is to provide a comprehensive training experience that prepares postdoctoral fellows for success in a variety of careers. All aspects of applications to the program are judged through this lens.
This program includes:
- research project in statistical sciences (actuarial science, biostatistics, data science, statistics)
- an interdisciplinary or applied collaboration or interaction.
- teaching experience; broadly-defined, that is equivalent to 1-2 courses over two years
- opportunities for professional development.
- a competitive salary.
The research project will be in the statistical sciences, and fundable by the Natural Sciences and Engineering Research Council of Canada (NSERC).
Substantial research progress should be feasible within the timeline of the postdoctoral fellowship. The roles of the supervisor and co-supervisor must be clearly defined, along with how they will interact with each other and the postdoctoral fellow.
A description of how the postdoctoral project relates to any research support of the supervisors should be included in the application.
Interdisciplinary or Applied Experience
The postdoctoral fellowship will include a significant interdisciplinary or applied component.
The postdoctoral fellowship will include a significant interaction with a researcher, organization or group directly related to the research project (experiments, data and application).
The proposed experience should contribute to the overall training of the postdoctoral fellow and fit well with the statistical research.
The Co-supervisor may come from another discipline.
Educational and communication activities should provide the postdoctoral fellow with the opportunity to gain important teaching and mentoring skills. The amount of activity is the equivalent of teaching one to two courses over two years, but there is considerable flexibility in the specifics.
- Teaching a three-credit, one-semester course
- Participating as a mentor in a CANSSI-sponsored summer training program.
- Mentoring teams of undergraduate or graduate students in project-based studies.
- Co-teaching with experience faculty
Professional Development & Mentorship
A mentoring plan should describe activities that support the professional development of the postdoctoral fellow.
- Development of skills and intellectual pursuits fitting a long-term career plan.
- Professional development and career preparation.
- Development of networking, collaboration, and partnership skills.
- Development of language and communication skills.
- The learning environment and opportunities for enriching the experience of the postdoctoral fellow at the host institutions.
Supervisor & Co-supervisor
The Supervisor will be an Associate Professor or Professor in statistics or biostatistics at a Canadian university, with experience supervising Ph.D students and postdoctoral fellows.
The Co-supervisor will be employed at a Canadian institution. In the case that the Co-supervisor is not in a university, a description justifying the proposed arrangement and describing the Co-Supervisor’s capacity to supervise research of a postdoctoral fellow is required.
Supervisors and co-supervisors may be listed on only one project. Current supervisors or co-supervisors of CANSSI distinguished postdoctoral fellows are not eligible.
Note: The supervisor and co-supervisor may both be Assistant Professors, provided that a more senior colleague (i.e. someone in statistics or biostatistics at a Canadian university at the Associate professor or full-professor level) is included as a mentor on the project. The mentoring plan for the postdoctoral fellow should include plans for how the more-senior colleague will be integrated into the project.
- Applicants must have a PhD degree in statistics, biostatistics, actuarial sciences, or data science.
- Your thesis must be successfully defended before September 30, 2023.
- Additional requirements:
- Applicants must not have already received a postdoctoral grant (including a Banting Postdoctoral Fellowship) from SSHRC, NSERC or CIHR.
- Applicants must have completed all requirements for a doctoral degree no more than two years before the deadline date of the year of application. Completion is considered as the date that all the requirements for the degree were met, including the successful defense and submission of the corrected copy of the thesis. This is not the conferred or convocation date indicated on your transcript. For applicants with more than one doctoral degree, the completion date of the most recent doctoral degree is used to determine eligibility.
- Applicants must submit proof of eligibility by October 15, 2023. Please contact email@example.com regarding questions about eligibility.
- CANSSI extends the eligibility period to three years for applicants
- that have acquired at least six months of full-time, relevant employment in industry or government after receiving a doctorate. Experience in an academic institution or its affiliated hospitals, research institutions and other laboratories will not be considered.
- that have completed a non-research based clinical residency program after receiving a doctorate.
- that have had their careers significantly interrupted due to parental, medical and/or family-related responsibilities.
- CANSSI extends the eligibility period to six years for applicants that have, within two years before or after the date of completion of a doctorate, become the primary caregiver following the birth or adoption of a child.
Requests for an extended eligibility period, may require additional information and/or supporting documentation. Such information is only used to assess eligibility.
If you wish to inform the review committee of delays and/or circumstances that may have affected your performance and/or productivity, please add a (“Special Circumstances”) section to your application (maximum ½ page).
CANSSI Ontario Postdoctoral Fellowship in Statistics
As part of the CDPF program, CANSSI Ontario and CANSSI have partnered to offer the CANSSI Ontario Postdoctoral Fellowship in Statistics. This fellowship supports research projects that deepen our understanding of theoretical statistical sciences, but projects in other areas of statistics may also be considered. If you are a faculty member at a CANSSI Ontario partner university or at an affiliated research institute, you are eligible to apply. See here for more details.
If you would like to apply for either the CANSSI national program or the CANSSI Ontario Postdoctoral Fellowship in Statistics or both, please refer to the “How to Apply” section below.
How to Apply
The application process for this program involves two stages. The first stage is the call for faculty proposals, where eligible faculty submit their research and training projects. Successful proposals move onto the second stage, where eligible Postdoctoral Fellows are recruited.
The Postdoctoral Fellow salary will be up to $70,000 per year plus benefits (worth approx. $14,875). The CANSSI grant will provide the majority of the salary and benefits, but will be supplemented by the following contributions:
- The host institutions (departments, colleges, and/or universities) will contribute up to $16,000 total salary over the two years for the teaching component.
- Supervisors, co-supervisors, and interdisciplinary partners will contribute 1-4 months salary total (over the two years).
- Research support of up to $3,000 per year (for computer, travel, supplies, etc.) will be provided by the supervisor, co-supervisor or their institutions.
Project List for 2022 (in English only):
- Comprehensive Risk Modeling and Trajectory Prediction of Diabetic Retinopathy Using Big Data
- Comprehensive Statistical Modelling for Radiobiological Changes Measured via Raman Spectroscopy
- Estimating COVID-19 Prevalence in Homeless Populations
- High-Dimensional and Matrix-Variate Copula Modeling
- Mixed High-Dimensional Copulas for Multivariate Time Series in Public Health (English or French)
- Multiple and Reliable Backtesting of Risk Measures
- Real-Time Multi-Scale Estimation and Uncertainty Quantification in Infectious Disease Models
- Statistical Foundations of Invariant Representation Learning, with Applications to Data-Driven Compression and Algorithm Design
- Statistical Methods for Daily Mortality and Multiple Environmental Risk Factors
- Zero-Inflation in Multinomial Principal Component Analysis for Microbiome Data
- CANSSI ONTARIO Postdoctoral Fellowships – Statistical Modeling and Feature Extraction for Large-scale Functional Data