Turn Theory into Practice with a PhD Internship
Are you a doctoral student looking to turn your PhD theory into practice? Read on to find out more about applying for a PhD internship which can give you industry experience – and more!
APR.Intern is the only national all sector-all discipline PhD internship program placing PhD students into short-term 3-5 month industry and university research collaborations. The Program currently has 40+ internship opportunities with industry partners including ANZ, Commonwealth Bank, CSL, DST Group, Meat & Livestock Australia and Shoal Engineering. View all the available internships here.
APR.Intern STEM PhD Internships
APR.Intern is a not-for-profit program driving innovation through industry and university research collaborations. It aims to connect PhD students and their academic mentors to industry partners and is open to women and men with an emphasis on gender equity, domestic, regional, Indigenous and disadvantaged PhD students into STEM internships.
RESEARCH FOR IMPACT
Turn PhD theory into practice on an industry problem
Explore tailored project arrangements
FAST TRACK CAREER
Build industry networks and enhance CV
Develop soft skills to complement research expertise
RECEIVE A STIPEND
Earning potential of $9k-$15k over 3-5 months
More than 40 internships are currently available. These are some of the openings available, and the STEM background you need to apply:
Background: Computer Science, Data Science
Commonwealth Bank is one of Australia’s leading providers of integrated financial services. The Net Promoter Score (NPS) is an industry-wide tool measuring customer advocacy for a brand. Each customer’s response shows their likelihood to recommend the organisation to others. NPS is important for CommBank, Australia’s largest bank, and is used to help drive improvements in our products, services and customers’ financial well-being.
This project is an opportunity to do some innovative research to predict NPS from social media data before formal NPS results are published while working inside one of Australia’s largest data science teams.
Background: Biomedical Science
CSL Limited is a global biotechnology manufacturer that researches, develops and markets products to treat and prevent rare and serious diseases.
This project will investigate Thrombin Generation (TG) – a laboratory method that is increasingly being used in multiple clinical settings for evaluation of bleeding and clotting outcomes. Whilst TG provides a global assessment of haemostasis, the main problem associated with this laboratory method is the lack of standardisation.
Background: Environmental Science, Agricultural Science, Economics, Engineering
Meat & Livestock Australia (MLA) is a leader in delivering world-class research, development and marketing outcomes that benefit Australian cattle, sheep and goat producers.
This project follows a successful APR internship earlier this year and involves the development of a triple bottom line approach to measuring and evaluating the impact made under MLA’s Environmental Sustainability Program over the financial years 2016-17. This will require the development of economic, environmental and social metrics.
Background: All STEM
The Defence Science and Technology Group (DST) is the Australian Government’s lead agency responsible for applying science and technology to safeguard Australia and its national interest. As one of Australia’s largest employers of scientists and engineers, DST deliver expert, impartial advice and innovative solutions for Defence and national security.
There are currently multiple STEM PhD internship opportunities with DST including projects in computational underwater acoustics and adaptive automation in next generation human robot teaming.
Background: Software Engineering, Computer Science, Bioinformatics
iugotec is a sensor technology company that designs, develops and deploys next-generation chemical sensing solutions to solve complex problems. This is achieved by integrating advanced sensing technologies, electronics and software.
This project will integrate machine learning capability into the data analysis step to facilitate autonomous real-time machine learning and decision making.
Author: Larissa Fedunik-Hofman
Larissa is the editorial assistant for Careers with STEM and a Chemistry PhD student. Larissa’s goal is to promote public engagement with STEM through inspiring stories.