APR.Intern - Industrial Monitoring and Control
External opportunities: These internships are not automatically approved for course credit as we do not have a formal agreement with the host organisations. They are considered as self-sourced internships and if they meet the requirements for project content, learning outcomes, safety, etc they can be considered for credit.
If you negotiate a self-sourced internship, email science.internships@anu.edu.au to enquire about credit. Contact us as soon as possible so we can assess the internship requirements, and enrolment in the internship course (eg SCNC 3000) arranged for credit. Include this information in your email: Name of Host organisation; Address of Host organisation; Title of project; Description of project and your duties; Clearances required; Host Supervisor contact details: name, address, email address and phone number; Number of units; Intended session/year of internship eg. Semester 1, 2021.
Internship type
Credit
Level
Description
Industrial Monitoring and Control is looking for a PhD student who meets some or all of the criteria below:
- Interest in conservation and marine species.
- Mathematics, engineering, software programming or data science background; particularly in the areas of computer vision and AI/ML model development.
- Programming and technical skills in Python, MongoDB and AWS are beneficial.
Full details of the internship project, including duration, eligibility, scholarship and application can be found at:
https://aprintern.org.au/internship/industrial-monitoring-control-apr-1949/
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The application process differs depending on whether the placement is advertised or you find it yourself.
