This position is offered through the ANU Computing Internship courses (COMP3820 / COMP4820 / COMP8830).
Semester 2, 2023 applications open on Tuesday 23 May and close on Monday 29 May.
Company
Borevitz’s Lab/The Research School of Biology (RSB) is one of the eight research schools in the Australian National University’s College of Science. It was established in 1946 and is located on the ANU campus in Canberra, Australia.
Project—Employing Machine Learning to Support Renewable Energy Transition in Australia
The intern will be involved in an exciting, cutting-edge project aimed at advancing the transition to Renewable Energy in Australia. This project leverages data analytics and machine learning to devise policy interventions that promote this transition. The intern’s task will be to apply supervised and unsupervised machine learning methods, association rule learning, and causal inferences to analyze survey data. This data will help to understand the factors that influence communities’ ability and willingness to transition to renewable energy sources.
The intern’s primary responsibilities will include:
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Applying and refining machine learning models to this data.
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Identifying patterns and associations that can inform recommendations.
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Using causal inference to identify the impact of potential interventions.
The goal is to facilitate the development of data-driven, tailored policy interventions that effectively support the RE transition across Australia.
Required technical skills
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Proficiency in Python, particularly with libraries such as pandas, numpy, scikit-learn, TensorFlow, and keras for data manipulation and machine learning.
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Experience with unsupervised and supervised machine learning algorithms.
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Familiarity with association rule learning and causal inference.
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Experience with data visualization tools, such as Matplotlib, Seaborn or Plotly.
Required/preferred professional and other skills
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Strong analytical and problem-solving abilities.
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Ability to work independently and as part of a team.
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Excellent communication skills, with the ability to present complex data in a clear and accessible manner.
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High level of attention to detail, accuracy, and organization.
Delivery Mode
Remote (Intern engages on project in a remote capacity)
Student location
Students located within Australia
Project’s Special Requirements/ Conditions
None
Type of internship
Unpaid placement
How to apply
Applications are invited from eligible students to apply for the Computing Internship courses COMP3820 or COMP4820 or COMP8830. Eligibility details of COMP3820 / COMP4820 / COMP8830 and further information about the Computing Internship can be found on the Computing Internship page.
Eligible students can apply through the Computing Internship application form which will be available via the Computing Internship page between Tuesday 23rd May 2023 to Monday 29th May 2023.
You can nominate multiple preferred Internship projects and host organisations through the one online application form.
Eligibility and Room Available in degree to undertake COMP3820/COMP4820/COMP8830 will be assessed at the time of application. If you do not meet the eligibility criteria or do not have room in your degree to fit COMP3820/COMP4820/COMP8830, your application will not be progressed.
Your application will require you to upload the following documents:
- an updated copy of your Resume, and
- an Expression of Interest (limit 350 words) for each organisation you wish to apply to (for organisations with multiple projects only submit one Expression of Interest but state clearly which project/s you wish to be considered for).