Acoustic Data Scientist / Deep Learning Developer

MERIDIAN is a consortium of ocean researchers, computer scientists, and data managers building a Canadian data infrastructure for underwater acoustics data and vessel tracking data. For more information, please visit our homepage: https://meridian.cs.dal.ca

Job Summary

Reporting to the Senior Staff Scientist, the Acoustic Data Scientist / Deep Learning Developer will work alongside a multidisciplinary research group in developing novel analytical software to support ocean researchers in tracking the movements and study the behaviour of marine animals through the sounds that they produce underwater. In particular, the Acoustic Data Scientist / Deep Learning Developer will develop and train deep learning models at detecting and classifying the vocalisations of marine species such as killer whales and North Atlantic right whales.

Key Responsibilities

• Engage with ocean researchers to understand their needs as they relate to analytical software and deep learning models.

• Collaborate with ocean researchers on building acoustics training and test datasets for machine learning applications.

• Develop and train deep learning models for detecting and classifying sounds.

• Produce documentation for team members, code repositories, and end-users.

• Envision new tools and features that make use of available data and resources.

• Contribute to the development of MERIDIAN data analytics packages, esp. Ketos.

Note

The successful applicant will work remotely through the period of COVID restrictions. After restrictions are lifted, the successful applicant may work on campus or continue to work remotely, as agreed by all parties based on operational requirements.

Qualifications

Masters of Science in Computer Science, Data Science, Physics, Oceanography, Mathematics, Statistics, Marine Biology, or a closely related discipline with demonstrated experience with data analytics and machine learning is required. Experience with deep learning, knowledge of Python and Tensorflow (or another Deep Learning framework), familiarity with acoustics data, and the physics of sound propagation are considered important assets. Familiarity with command line and basic program installation/configuration on remote servers, experience using Git, and storing code in repositories (GitLab) are preferred. Must have the ability to work independently while coordinating with other team members where work overlaps and be able to prioritize the workload to ensure deadlines are met.

Additional Information

Dalhousie University supports a healthy and balanced lifestyle. Our total compensation package includes a voluntary RRSP, health and dental plans, and an employee and family assistance program.

Application Consideration

We thank all applicants for their interest, however, only candidates selected for an interview will be contacted.

Diversity Statement

Dalhousie University is committed to fostering a collegial culture grounded in diversity and inclusiveness. The university encourages applications from Indigenous persons, persons with a disability, racially visible persons, women, persons of a minority sexual orientation and/or gender identity, and all candidates who would contribute to the diversity of our community. For more information, please visit www.dal.ca/hiringfordiversity.