Simon Fraser University, Mathematics

Fellowship ID:

SFU-PDF1 [#27974]

Fellowship Title:

SciML Postdoctoral Fellowship – Numerical Weather Prediction (Canadian Arctic)

Fellowship Type:

Postdoctoral

Fellowship Location:

Burnaby, British Columbia V5A 1S6, Canada

Subject Area:

Mathematics

Appl Deadline:

2026/02/07 11:59PM help popup

(posted 2026/01/12, listed until 2026/02/07)

Fellowship Description:

POSTDOCTORAL FELLOWSHIP:

Hybrid Scientific Machine Learning + Numerical Weather Prediction (Canadian Arctic)

Department of Mathematics | Simon Fraser University (SFU) | Metro Vancouver, BC, Canada

Simon Fraser University’s Department of Mathematics invites applications for a Postdoctoral Fellowship (PDF) to work on hybrid scientific machine learning (SciML) and numerical weather prediction (NWP), with a particular focus on the Canadian Arctic. This is part of a collaboration between Professors Ben Adcock (ben_adcock@sfu.ca) and Steven Ruuth (steven_ruuth@sfu.ca) and Environment and Climate Change Canada (ECCC).

Accurate forecasts in the Canadian Arctic are critical for the safety, food security, and resilience of Inuit Nunangat communities. This project aims to fuse traditional numerical methods with machine learning techniques, such as operator learning and active learning, to enhance predictive capabilities in regions where traditional weather prediction performs poorly. This position is part of a larger, multi-institutional initiative on hybrid ML–NWP across Canada.

We seek applicants with outstanding research potential and the initiative to help drive a collaborative agenda. The successful candidate will contribute to an ambitious hybrid ML–NWP program and will have significant scope to shape an independent research direction aligned with the project’s goals. They will also be an integral member of the group—mentoring graduate and undergraduate trainees, helping to build shared research infrastructure, and fostering a collegial, inclusive environment that supports high-quality scholarship and real-world impact.

Impact+ nomination and stipend

SFU will nominate the selected candidate for a Canada Impact+ Research Training Award (Postdoctoral), subject to eligibility and internal selection. These awards are valued at $70,000 per year for two years.

Program details (official):

• Canada Impact+ Research Training Awards:

https://sshrc-crsh.canada.ca/en/funding/opportunities/canada-impact-plus-research-training-awards.aspx

• Q&A (official):

https://nserc-crsng.canada.ca/en/canada-impact-research-training-awards-qa

Appointment, start date, and teaching

• Duration: up to two years (initial 12-month appointment, renewable for a second year).

• Anticipated start date: July 1, 2026 or September 1, 2026 (flexible).

• Teaching: the fellow may have the opportunity to teach up to one undergraduate course per year (by mutual agreement; teaching is not required for success in the role and will be arranged separately).

Qualifications

Excellence in research is the primary criterion. Applicants must:

• Hold a PhD in mathematics, applied mathematics, computer science, atmospheric science, physics, or a closely related discipline by the start date.

• Have a strong research record in one or more of: scientific machine learning, numerical PDEs, numerical weather prediction, or related areas.

• Demonstrate strong scientific computing skills (e.g., Python and modern ML frameworks).

• Communicate effectively and thrive in a collaborative, interdisciplinary environment.

Eligibility

• Nominees can be of any citizenship, including Canadian citizens, permanent residents, and protected persons.

• Nominees cannot have a current affiliation with a Canadian institution and must be currently studying or working abroad.

How to apply

Applications must be submitted online via MathJobs: [INSERT MATHJOBS URL]

Reference letters must also be submitted through MathJobs.

Full consideration will be given to applications received by January 31, 2026.

Please include:

• Cover letter (max 2 pages) describing fit with the position and your interest in Arctic-focused hybrid ML–NWP.

• A complete, up-to-date curriculum vitae that lists the candidate’s education and employment history, publications, conference presentations, funding and awards, student supervision, collaborations and partnerships, teaching experience, and service activities if any.

• Research statement (2–4 pages) describing prior work and a proposed research plan.

• Two examples of published or submitted scholarly work (or links to preprints).

• Teaching statement (optional; submit if you wish to be considered for teaching opportunities).

• Three reference letters submitted through MathJobs.

Equity, diversity, and inclusion

SFU is an equity employer and strongly encourages applications from all qualified candidates, including women, Indigenous Peoples, racialized persons, persons with disabilities, and people of all sexual orientations and gender identities.

Privacy notice

Personal information submitted as part of an application will be used for the purposes of assessment and selection in accordance with SFU policies and applicable privacy legislation.

Application Materials Required:

Submit the following items online at this website to complete your application:

Cover letter
Curriculum Vitae
Research statement
Teaching statement
Two examples of published or submitted scholarly works
Three reference letters (to be submitted online by the reference writers on this site )

And anything else requested in the fellowship description.

Further Info:

http://www.math.sfu.ca/

Simon Fraser University
Department of Mathematics
SCK 10512
8888 University Drive
Burnaby, BC V5A 1S6