[MARMAM] Postdoc in Machine Learning and Killer Whale Acoustics
rjoy at sfu.ca
Mon Jun 22 11:01:42 PDT 2020
We are pleased to announce the following position for a Postdoctoral
Researcher. We welcome all applicants, however due to COVID travel
restrictions, if you are not in Canada already, please check if you are
able to obtain a work permit and travel provisions for Canada.
Only 72 Southern Resident Killer Whale individuals remain as of February
2020, the population cannot risk any injuries or mortalities from ships
that transit through their habitat. The goal is to automatically detect
whale sounds from underwater acoustic signals so as to alert ships of their
presence to reduce the risk of collisions. The research goals involve
development of machine learning tools for under-water acoustic signals and
extend into uncertainty quantification and sequential experimental design.
A deep learning approach will be used to develop a whale detector from a
catalog of labelled sounds from different killer whale types and ambient
sounds. In order to validate and improve the whale detector, an active
learning (human-in-the-loop) approach will be developed to prioritize new
annotation tasks for the human analyst. The end result will be integrated
into open-source software, including a plug-in for PAMGuard for use by
people working in marine mammal acoustics.
There is room for applied and methodological research.
Ruth Joy, Department of Statistics and Actuarial Sciences and the School of
Environmental Science, Simon Fraser University
Dave Campbell, School of Mathematics and Statistics, Carleton University.
Oliver Kirsebom, Marine Environmental Research Infrastructure for Data
Integration and Application Network (MERIDIAN), Dalhousie University
Fabio Frazao, Institute for Big Data Analytics, Dalhousie University
*Steven Bergner*, Big Data Centre, Simon Fraser University
*Scott Veirs*, Orcasound open-source software project
What the supervisors are offering:
The intent is to build your research program, boost your employability, and
build your professional network, while saving the whales. This
post-doctoral opening is designed to ensure collaborative and networking
opportunities for the candidate. There is a clear target research project,
but the candidate will have academic freedom to become involved in other
research projects that align with their career goals.
Opportunities to Build Academic Collaborations Across Canada:
When travel becomes realistic once again, the project has funding for the
candidate to spend collaborative time at Simon Fraser University, as well
as Dalhousie University. We want to help you to develop career connections
While being hosted in Ottawa, the candidate will be introduced to a network
of collaborators at government research labs such as the National Research
Council of Canada and Department of Fisheries and Oceans, as well as other
Salary: $65,000 per year plus travel.
Project duration: 2 years
Location: Carleton University, Ottawa but we understand the world is
strange these days and needs some flexibility.
- The candidate must have experience working with real data.
- The candidate must have strong computing skills in R and/or python.
- The candidate should have a skillset emphasizing computational
statistics, statistical computing, and/or machine learning.
- The candidate would ideally have interests / strengths in some of:
statistical algorithms, high performance computing, audio signal
processing, ecological modelling, computational statistics, state space
modelling, Bayesian sampling algorithms, or hierarchical modelling.
Send an email to:
RuthJoy <rjoy at sfu.ca> and DaveCampbell <davecampbell at math.carleton.ca>
With the subject “Postdoc: Save the Whales”, please include your potential
start date in your cover letter.
Deadline: July 15th, 2020, or until the position is filled.
For any questions do not hesitate to contact me.
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