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<b><h4>Briefly describe your collaboration and why it was felt that working in a collaboration would be more effective than working alone to resolve your research question.</h4></b>

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<b>Dr Peter Hristov, Postdoctoral Research Assistant, University of Liverpool</b>

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Work in my field of research, it tends to be very multidisciplinary. For example, I'm an engineer, but I also tend to work in applied mathematics or in statistics. And I found that you cannot, you just cannot, know everything that you need to progress your work.

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So for example, on a regular basis I would consult, during this project specifically, aerodynamicists or structural engineers or bioengineers, mathematicians, statisticians, physicists, and all sorts of other people. And I think it's very important to have a varied partnership of collaborators, so that you can reach out to those with better expertise when the time arises for you to ask questions along your research.
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<b><h4>How was information or data collected, stored and shared?</h4></b>

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<b>Dr Peter Hristov:</b> When participating in research projects, sharing data is inevitable, but it's oftentimes also the most sensitive part of the project. This is because every partner would have something valuable and proprietary to add to the work so that it progresses. The situation is complicated even further when industry is in the project. This is because potential leaks in data can cost them millions of pounds.

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So what I tend to do is, when I store information, I use secure repositories that provide the maximum protection that is available there. And when I share it, it's usually via encrypted connections. 
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<b><h4>Did the collaboration pose any administrative challenges, such as differences in regulations or hiring and accounting practices? If yes, how did you deal with them?</h4></b>

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<b>Dr Peter Hristov:</b> Regulations definitely do exist, especially when we talk about differences between academia and industry. In my experience, these differences would mainly be in terms of again, data sharing, and access to data or models, and similar things. However, in my practice, this has never been an issue. 