Ministry of Water, Land and Resource Stewardship

This position can be based in any of the following Ministry of Land, Water and Resource Stewardship offices: Burns Lake, Smithers, Terrace.

Flexible work options are available; this position may be able to work up to 2 days at home per week subject to an approved telework agreement.

Aquatic Ecosystem Specialist

$85,813.18 - $97,879.22 annually, which includes a 3.3% Temporary Market Adjustment*, plus

$37.64 bi-weekly isolation allowance for Smithers; $41.07 bi-weekly isolation allowance for Burns Lake.

The Ministry of Water, Land and Resource Stewardship is accountable for integrated land and natural resource management, including objective setting for terrestrial, aquatic and marine environments, effectively managing cumulative effects, and advancing reconciliation with Indigenous peoples, environmental sustainability, and economic growth.

The Aquatic Ecosystem Specialist is a regional scientific advisor in the field of natural resource management. This role provides expert professional advice relating to fish and aquatic habitat, watershed management, and undertakes projects that support science-based decision-making.

Qualifications for this role include:

• Undergraduate Degree or higher in biological sciences or equivalent (e.g., natural resource management, ecology, zoology) and 5 years of related experience*
• Registered (or immediately eligible) as a Registered Professional Biologist (RP Bio) in B.C. with the College of Applied Biology within six months of employment.

Note: Immediately eligible is defined as being registered as a Professional Biologist (RP Bio) with the College of Applied Biology within 6 months of appointment. Confirmation of registration/eligibility will be required before an offer of employment can be confirmed. If you are not currently registered, advise how you have confirmed with the CAB that you are immediately eligible.

*5 years of Related Experience (or an acceptable combination of education and experience) in each of the following, or a combination totalling a minimum of 5 years:

• Experience in conducting fish or aquatic habitat surveys, environmental monitoring, assessments and reporting.
• Experience interpreting, applying, or providing advice on natural resource management legislation and/or policy.
• Experience working on multidisciplinary teams and/or with diverse stakeholders.
• Experience collaborating and/or consulting with First Nations on resource management issues.

For more information and to apply online by July 4, 2024, please go to:

https://bcpublicservice.hua.hrsmart.com/hr/ats/Posting/view/113782

Company Background

We are a distributed, passionate and fun team based in Canada/USA and incubated by IBET to

create commercially scalable gigaton solutions to the climate crisis. This critical role will join the Skyward team to prevent lightning-caused wildfires, just as the team moves from lab to the cloud!

Why Fire? Why Lightning? In 2023 alone, Canada’s wildfires burned 5% of its forests (an area the size of Washington State) and released ~5% of global emissions (almost as much as India’s 2023 emissions and 3 times Canadas). Over 60% of fires are caused by lightning strikes, and 93%-97% of the burn area and emissions are lightning-caused, with ignitions predicted to increase sharply with global warming. Wildfires currently cost US and Canadian taxpayers hundreds of billions, with no end in sight. While efforts are being made to counter megafires through beneficial fire and improved forest management, Skyward can prevent lightning now, on-demand, and thus avoid forest fire emissions and buy humanity more time to solve our climate crisis.

The Skyward Solution is an integration play building on existing hardware, data, algorithms, and materials, all of which are safe and extensively reviewed for environmental and health impacts by governments. Because nobody has ever avoided fires this way, we are trailblazing. The Province of Alberta, which had 1,092 fires in 2023, impacting 48 communities, with 38,000 evacuations and 2.2m ha burned, has asked us to prevent fires this summer 2024 during peak lightning season.

Job Overview

As the Chief Science Officer (CSO), you will be a key leader in our company, responsible for overseeing the development and deployment of cutting-edge weather modeling, intervention siting and targeting, and lightning forecasting technologies. You will lead efforts in building predictive models for fire risk, lightning prediction, and weather forecasting, as well as targeting interventions and siting deployments. You will develop licensable software and intellectual property. This role is crucial in shaping the company’s technological strategy and ensuring our solutions are both innovative and highly effective so governments, citizens, and industry partners can count on us.

Key Responsibilities

• Model Development: Lead the development and implementation of advanced AI and ML models for accurate weather forecasting, lightning prediction, cloud modeling, wildfire risk assessment, and intervention siting and cloud deployment.
• Commercialization: Design and deploy cloud-based solutions with client-facing interfaces
• Team Building: Build, manage, and mentor a high-performing data science team, fostering an environment of innovation and excellence.
• R&D: Drive the creation of licensable software products and manage intellectual property development aligned with strategic business goals.
• Collaboration: Engage with cross-functional teams including R&D, operations, and business development to ensure technology alignment with business needs.
• Innovation: Stay abreast of the latest technology trends and advancements in AI, ML, and meteorological science to continuously innovate and improve our solutions.
• Quality: Ensure accuracy and reliability in predictive models and data-driven decisions.
• Communication: Present complex technical information to stakeholders and external partners in a clear and effective manner.

Requirements

• Education: Master’s or PhD in Computer, Data or Atmospheric Sciences, or related field.
• Experience: Proven experience as a CTO/ CDO/CSO, or similar leadership role, in technology-driven companies, ideally within weather-related industries.
• Technical Skills: Demonstrated proficiency in AI and ML, with experience in developing and deploying predictive models. Experience with weather modeling, atmospheric science, etc
• Leadership: Exceptional leadership building and managing high-performing teams. Demonstrated ability to think strategically and drive technological innovation.
• Entrepreneurial: strategic mindset with the ability to work in a fast-paced startup.
• Communication: Excellent communication and interpersonal skills, with a talent for bridging technical and business perspectives.
• Travel: periodic travel to meet customers, team, attend Board Meetings, etc.

What we Offer

• A unique opportunity to create technology that protects the environment and communities.
• Competitive compensation package, including equity.
• Flexible working conditions with opportunities to work remotely.
• A dynamic and supportive team culture that values innovation, performance, and fairness.

How to Apply

Email sgoldman@ibetclimate.com with your resume and a cover letter sharing your experience with AI / ML technologies, leadership in technology teams, and your background in weather modeling.

Join us in our mission to revolutionize wildfire prevention and support our planet’s future.

We cordially invite applications for four (4) postdoctoral and three (3) PhD student positions to work in the areas of weather forecasting, climate modeling, satellite data analysis and comparison, to aid the science development of a new Earth-observing satellite.

Research description

Joining the leadership in the space observations of climate change, Canada will contribute three instruments, TICFIRE (Thin Ice Cloud and Far InfraRed Emissions), ALI (Aerosol Limb Imager) and SHOW (Spatial Heterodyne Observations of Water), jointly known as HAWC (High-altitude, Aerosol, Water Vapour and Clouds), to co-fly with the other instruments in the NASA-led satellite mission: the Atmosphere Observing System (AOS).

The successful candidates will join the Canadian HAWC Science Development Team (SDT) funded by the Canadian Space Agency and steered by the HAWC Canadian University Consortium, to undertake a suite of science development activities that are crucial to developing the sciences and applications of the AOS/HAWC measurements. A total of seven positions are open in this initial round of SDT recruitment, including four postdoctoral researchers and three PhD students. Each hire will be appointed at McGill University, University of Toronto, or University of Waterloo, to focus on one of the research subprojects outlined below.

1. Thermodynamic and radiative anomalies of weather extremes

Subproject lead: Professor Yi Huang (yi.huang@mcgill.ca)

Positions open: one postdoc and one PhD student

Location: McGill University, Montreal, Canada

Objective: this research will assess thermodynamic and radiation anomalies in extreme events such as overshooting convections and cold air formation/outbreaks, using climate and radiative transfer modelling.

2. Trajectory hunting investigations for comparing HAWC data

Subproject lead: Professor Kaley Walker (kaley.walker@utoronto.ca)

Positions open: one postdoc

Location: University of Toronto, Toronto, Canada

Objective: this research will investigate methodologies for satellite data comparisons by using trajectory hunting techniques and explore how these can be used for HAWC measurements.

3. Satellite detection of snowfall and snow accumulation across Canada’s North

Subproject lead: Professor Christopher Fletcher (chris.fletcher@uwaterloo.ca)

Positions open: one postdoc and one PhD student

Location: University of Waterloo, Waterloo, Canada

Objective: this research will develop new optimal retrieval algorithms for satellite detection of snowfall and snow accumulation across Canada's North by using instrument simulators and machine learning.

4. Cloud feedback and its far-infrared signatures in GCMs

Subproject lead: Professor Ivy Tan (ivy.tan@mcgill.ca)

Positions open: one postdoc and one PhD student

Location: McGill University, Montreal, Canada

Objective: this research will evaluate the Arctic cloud feedback in the Canadian climate model in connection with the representation of black carbon in particular.

Postdoctoral Researchers

Salary (including benefits): $60,000CAD/year

Expected start date: ASAP

Term: One year, renewable up to 2.5 years

PhD Students

To apply for the PhD positions, interested applicants are encouraged to first contact the leads of the subprojects of their respective interests. Please send a recent academic transcript, an updated resume, and a half-page statement of research experience and interests. The successful candidates need to meet the admission requirements of the respective universities. More information can be found at the following websites:

• McGill University/Department of Atmospheric and Oceanic Sciences: https://www.mcgill.ca/meteo/programs-0/graduate-studies/graduate-programs
• University of Waterloo/Department of Geography and Environmental Management:

https://uwaterloo.ca/graduate-studies-postdoctoral-affairs/future-students/programs/geography-phd-waterloo

Salary and benefits: set by each institution

Expected start date: January 1, 2025 (Note: application deadlines for PhD programs vary by institution and should be discussed with the lead from the appropriate institution).

How to apply

To be considered for the postdoc positions, an applicant must have a Ph.D. degree in atmospheric sciences, meteorology, physics, or a related discipline, received within the past 4 years (after January 1, 2020). The candidate shall have the ability to conduct original and independent scientific research and is expected to have experience in one or multiple of these skills:

• global or regional weather and climate modelling,
• radiative transfer modelling,
• trajectory modelling,
• satellite measurement simulation,
• analysis of model and/or satellite datasets,
• programming in Fortran, Matlab or Python on Linux systems.

Interested applicants are encouraged to directly contact the leads of the four subprojects of their interest by email, enclosing:

• a cover letter,
• a curriculum vitae,
• transcripts and academic records (B.Sc. and at the graduate-level), and
• names and contact information for at least two references.

An applicant can apply for one or multiple of these four subprojects simultaneously but is strongly recommended to clearly identify a primary subproject at the top of their application. The applications will be evaluated independently for each subproject. Evaluation of the applications will start once received and continue until all the positions are filled.

Yi Huang, McGill University

Kaley Walker, University of Toronto

Christopher Fletcher, University of Waterloo

Ivy Tan, McGill University

on behalf the HAWC SDT

SE-RES-1 (Postdoctoral Research Program)

Natural Resources Canada, Pacific Forestry Centre, Victoria, B.C.

Position Summary:

Natural Resources Canada (NRCan) is looking for a postdoctoral researcher to develop and apply statistical methods to predict the occurrence of severe wildfires in Canada. The researcher will work with fire scientists from NRCan and statisticians at the University of Guelph as part of an interdisciplinary “Daily Fire Occurrence and Burn Probability” project. 

We seek a statistician or a quantitative environmental scientist with expertise and interest in statistical methods relevant for environmental/atmospheric sciences. The position offers an excellent environment for working with a highly skilled interdisciplinary team in NRCan and at Guelph University. The expertise of team members includes applied statistical modelling, stochastic processes, machine learning, climate analyses, and wildfire behavior and occurrence prediction.  The successful candidate will focus on the analysis of the influence of weather and other environmental variables on the occurrence of lightning, human caused and severe fires, and the development of predictive models for such occurrence.  Understanding and predicting of severe fires is an area of intensive current research in the fire science community and critically important to public safety.

The position requires developing and applying a combination of statistical methods such as spatio-temporal statistics and machine learning, to estimate the probabilities of fire events under different atmospheric and environmental conditions.  A key focus will be to quantify the uncertainty in the probabilities in light of a wide variety of sources of uncertainty.  The researcher will evaluate, extend and implement existing methods and develop new statistical frameworks and methods to predict the occurrence of wildfires in relation to forecasted weather and other explanatory variables. The researcher will work with fire scientists to apply and to weather forecasts and implement them within in a wildfire information system.

Specific Responsibilities:

• Develop and apply statistical methods for prediction of the occurrence of severe wildfires.

• Compare predictions to past observations to evaluate the fidelity of models and examine the risk of model failure (false negatives)

• Produce and deliver oral and written presentations of scientific results.

• Work effectively in an integrated team.

Essential Qualifications:

• PhD in statistics, data science, environmental or physical sciences or a related field to be completed within the last 3 years and as of the start date for this position

• Experience in planning and conducting research

• Experience in working with a team of researchers and support staff

• Excellent written and oral communication skills

Additional Desired Qualifications:

• Proficiency with scripting languages such as R and/or Python; frameworks such as tidyverse and data visualization using ggplot2 or similar packages

• Ability to manipulate large datasets and data bases and carry out efficient computation

• Experience in one or more of the following areas: categorical data analysis, generalized additive models, statistical learning, spatial statistics, machine learning.
• Experience in environmental, forest or atmospheric science.

How To Apply:

• For information search for ‘Natural Resources Canada Post Doctoral Research Program’ for https://natural-resources.canada.ca/careers/graduates/postdoctoral-research-program/17880    
• To submit an application follow the “Apply Now” link  to https:\\nrcan-rncan.hiringplatform.ca/6355-postdoctoral-research-program-prp/20673-application-form/en
• In the Education section indicate a specialization in one or more of Mathematics, Forestry Science, Computer Science, Atmospheric Science and Meteorology, Physical Sciences, or Engineering and Technology at the PhD, Masters and/or undergraduate level.
• You will be required to upload a CV in the application.
• Contact  steve.taylor@nrcan-rncan.gc.ca indicating your interest in the position.

Notes:   

• The successful candidate will be hired as a term SE-RES-1 employee (salary range: $ 68,264 -90,463).
• This is a 1-year term position with renewal for an additional 18 months contingent upon satisfactory job performance and continuing availability of funds.  The position will be located in Victoria, BC.  The anticipated start date is September 1, 2024, but is flexible.
• Conditions of employment:  Reliability Status security clearance; English essential; willingness and ability to travel within Canada.
• The Postdoctoral Research Program (PRP) inventory list will be open for 5 years. 
• The PRP provides scientists with the opportunity to work with research groups or leaders in Canadian government laboratories and research institutions. In turn, the Government of Canada benefits from new and emerging talent.