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PhD scholarship opportunity

Networks and commercialising public research


Position: PhD with Scholarship & Top-Up Stipend


Location:        Centre for Transformative Innovation

Faculty of Business and Enterprise

Swinburne University of Technology

Melbourne, Australia


Supervisor: Dr Dean Lusher


Deadline for Expressions of Interest: 28 February 2014


This is an exciting opportunity to undertake a PhD on the social networks involved in the commercialisation of public research.


Australian Research Council (ARC) Future Fellowship Project:
Complex ties: Investigating the Role of Networks in the Commercialisation of Public Research


The PhD candidate will work on a project funded through an Australian Research Council (ARC) Future Fellowship Project Complex Ties: Investigating the Role of Networks in the Commercialisation of Public Research’. This project will research how interpersonal and inter-organizational collaboration networks are established and maintained when commercialising a product stemming from a public research invention. This will involve a systematic social network analysis of the complexities of forming and managing relationships for the commercialisation of technological innovation pioneered in Australia, across time and at comparative international sites - Australia, USA, UK, France, China and Japan. In doing so, this project seeks to understand the social search processes that lead to commercialisation success or failure in a competitive global economy.


The proposed project aims to identify activities that increase the ability to commercialise platform technology inventions from public research by understanding the social processes that lead to commercialisation success or failure in a competitive global economy. The project will identify specific efficient processes to enhance innovation, providing an opportunity to direct future industry policy formulation by examining the following:


1.    Do the distinct cultures of public research institutions and private firms foster organizational and personal identities that are antagonistic and so create barriers to trust and collaboration across these two domains?

2.    What kinds of interpersonal interactions and experiences foster trust between individuals in the two domains?

3.    Do the successful cases of public/private collaboration have (multilevel) network architectures, network motifs or structural logics that are (statistically) different from those of unsuccessful cases?

4.    How can we conceptualise the complexity of collaboration ties in commercialisation networks in terms of positive or negative relations, or some combination of the two, and the transitions between these that collaboration ties might entail, and their relation to commercialisation success or failure?

5.    How are the issues of geographical distance handled in the successful cases? Is this factor significant in the unsuccessful cases and, if so, what practical lessons should be taken from the successful ones?

6.    What are the dynamics in the various regions, with particular attention to differences between traditional commercialisation hubs in Europe and North America, and emerging ones in Asia?



The potential candidate has the opportunity to engage with one or more of the applied issues above, or work on the development of statistical network models that will facilitate the answering of these questions.


Swinburne node of MelNet

The PhD candidate will work with colleagues in the Swinburne node of MelNet (the other node being at the University of Melbourne). MelNet is a Melbourne-based consortium of universities with significant expertise in social network analysis, which conducts research and training in the theory, methods and applications of social networks. Collaborations between the MelNet nodes will also mean that the PhD student will also have access to one of the leading methodological groups in the world on network models.


The research team includes:

Dr Dean Lusher (Swinburne University of Technology)

Professor Michael Gilding (Swinburne University of Technology)

Dr Greg Simpson (CSIRO)

Dr Megan Fisher (CSIRO)

Professor Tom Spurling (Swinburne University of Technology)

Dr Ian Elsum (Australian National University)

Ms Vikki Bunton (Swinburne University of Technology)



Other researchers involved in the project include:

Professor Garry Robins, University of Melbourne

Dr Peng Wang, University of Melbourne

Dr Johan Koskinen, University of Manchester

Dr Bernie Hogan, Oxford Internet Institute

Professor Emmanuel Lazega, Paris Institute of Political Sciences

Professor Alessandro Lomi, University of Lugano



Candidate Requirements

Applicants will have an excellent academic track record with a bachelor’s degree with honours or a Master’s degree in Business, Economics, Sociology, Social Psychology, Statistics, Science, Engineering, or a cognate discipline. Alternatively, applicants may also have a wealth of practical experience and be looking for a career change. Applicants will be considered provided they fulfill the criteria for PhD admission and scholarship of Swinburne University of Technology and demonstrate excellent research capacity. The latest that this PhD can commence is 27 June 2014.




We offer a Swinburne University stipend to the value of $$25,392 per annum plus a top-up scholarship of $10,000 per annum for the three years of the PhD (2014 - 2017). The total value is $35,392 and is tax free.



Expressions of Interest (EOI)

Please send your CV, full academic track record, a synopsis of your research experience and a brief letter explaining why you want to work on this project (less than 1 page) to Dean Lusher ([log in to unmask]) by Friday 28 February 2014.


For more details about the project please contact Dean Lusher:  [log in to unmask]



Dr Dean Lusher

ARC Future Fellow

Centre for Transformative Innovation

Faculty of Business and Enterprise

Swinburne University of Technology

Hawthorn VIC 3122 Australia

T: +61 3 9214 5934 

E: [log in to unmask]



Check out our book on ERGMs: Lusher, D., Koskinen, J., & Robins, G. (2013). Exponential random graph models for social networks: Theory, methods and applications. New York: Cambridge University Press.


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