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AMSI Industry Internship Program
- new capability, insight and solutions
- industry experience
- access to hi-end expertise
- recruitment opportunities
- 50:50 funding support
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Why host an AMSI Intern?
- instant access to new high level expertise
- new skills funded 50:50
- excellent recruiting opportunities
- free access to university mentors
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Why be an AMSI Intern?
- add relevant industry experience to your CV
- establish professional networks
- up to $2,500 per month
- prospective long-term employment
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Why mentor an AMSI Intern?
- build new partnerships within industry
- participate in new and exciting projects
- receive $5,000 for co-supervision
- identify potential ARC Linkage grant projects
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Internship program details
- if you have
- a clearly defined research project
- an Industry partner
- a post-graduate student or research fellow from an AMSI member institution
- an academic mentor from an AMSI member institution
- You are eligible to apply. We will help you find any missing partner(s).
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Apply
- Download, read and complete as far as possible the
- 3-page Expression of Interest (EOI) form
- Terms and Conditions
- then e-mail them to Dr Thomas Montague at
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Opportunities - projects looking for participants
Industry Partner |
Intern |
Mentor |
Project Description | ||
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| 1. | IES | • |
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Energy trading | |
| 2. |
Department of Infrastructure | • |
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Transport models | |
| • partnering opportunities | |||||
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Calculating train running patterns to best meet demand
Mentor: Prof Phil Howlett, University of South Australia
Intern: Amie Albrecht
Industry Partner: TMG Rail Technology Pty Ltd
Project Duration: January to May 2008
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Passenger train timetables in Australia and elsewhere are manually developed every twelve months in response to infrastructure changes and fluctuations in demand. This project seeks to develop methods to calculate train running patterns that best meet demand. Methods to be developed will incorporate constraints such as train availability, capacity, track section running times, dwell times, rolling stock, track topology and capacity and the availability of staff. Findings are expected to lead to better, more robust train timetables. |
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