🎙️ Podcast Link 🎙️

This week I had coffee with a new colleague and the conversation got onto the realities and challenges of recruiting, and retaining, the talent you want to work with and need to fulfill all those exciting research, industry and government projects you’ve got going. Especially in topical fields with lots of competition for talent, and sky high salaries… 💲💲💲 

So late on this Friday afternoon and heading into yet another long weekend here in Brisbane, here’s my newest #HackingAcademia video covering talent strategy, including recruiting and retention considerations, and some of the things you can do about it, both now and longer term.

I cover:

🎓 In a typical academic career, you’ll run many research projects – fundamental, applied, with industry, government, or startups.

🧑‍🔬 Much of the work is done by recruited talent: PhD students, postdocs, RAs, engineers – so your ability to attract and retain talent is critical.

❤️ Some people are passion-driven – motivated by causes or purpose – and may be more tolerant of the inevitable imperfections in any role.

💼 Others are interest-aligned but pragmatic – and will not take a role, or leave, if conditions aren’t sufficiently attractive.

🌐 Your field’s opportunity landscape matters – are there lots of alternatives or only a few?

📣 Recruitment strategies vary. 🤝 Direct outreach and word-of-mouth can work in niche fields. 📢 For hot topics like AI, you may need (and benefit more from) broad, public exposure and a large network.

👤 Your reputation, your group’s alumni outcomes, and the broader ecosystem (faculty, university, country) all influence your appeal.

🌴 Culture and location can sometimes tip the balance, even if you can’t compete directly on salary.

🧱 Culture takes years to build – early-career academics should consider this before joining a new institution.

💰 Universities can’t match industry salaries – but be smart when writing grants. ✍️ Don’t under-budget salaries just to win the grant. ⚠️ Cutting salaries may create recruitment problems later.

🎯 Pitch a mix of projects. 🧪 Some high-risk, high-reward ones needing top-tier talent. 🛠️ Some more achievable ones suited to a broader skill range.

🌱 Avoid 100% “green fields” projects where neither you nor the student knows how to proceed when the going gets difficult.

🔄 Consider autonomy required, and provided. 🏃‍♂️ Some projects and talent that can operate without constant supervision are essential as you scale up.

🧮 Expand your recruitment pool. e.g. in a tech field: 🧑‍🏫 don’t only seek CS grads – consider rapidly upskilling engineers or mathematicians, who may come from (somewhat) less-in-demand talent pools.

🔁 Retention is just as important as recruitment. 🧲 Keeping good people saves time and effort. 🧳 But some turnover is healthy and inevitable.

🏡 Support retention by offering 🚀 growth pathways and professional development, and 🌏 a strong social and work environment – especially for newcomers.

💡 When designing a project or grant, always ask: 👥 What kind of talent will it require? 🔍 Is the pool broad or narrow? 🧠 How competitive is this space?

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Full Video Notes

In a typical academic career at a university you will run a number of research projects of various categories. They might be fundamental research projects funded by research bodies. They may be applied research projects with government or industry or startup partners. There will be a wide variety of them.

Common to almost all of these is that much of the work will typically be done by research talent that you recruit to that project. In many cases these are predominantly people like PhD students, masters students, research assistants, post-doctoral research fellows, and perhaps research engineers or software engineers.

So a large part of your success in your career will be determined by how well you can attract and recruit and importantly retain the talent you need in order to complete these projects successfully.

In today’s Hacking Academia video I want to talk about some of the things you can do to make your life easier in terms of recruiting and attracting and retaining talent. Some of these things will be activities that are very easy to do. Some of these will be longer-term more substantive things that you may not have complete control over, but they are all worth considering and thinking about as you refine your strategy for talent during your career.

One of the first things to consider is thinking about the nature of the work and research you do in your discipline and your sector, and the on-flow effects that has on the type of talent and the motivations of the talent who might work with you. To grossly simplify, you can really split this into two different categories.

The first is what I would call purely passion-driven endeavors. These are researchers that are strongly related to some sort of cause, often ideological or equity-based, that is very motivational for the people involved. This will attract people from all around the world and will often mean people move to suboptimal locations or roles because they really really want to work on that topic. Obviously you should not exploit that passion, but it is good to keep in mind that some people will be very very motivated to take a role with you in those areas even if some of the aspects of the role are not as optimal as they could be.

The second type of arguably more common role is interesting research roles that align with the sort of topics that the individual is looking for or interested in, but where if the conditions are too bad or there are too many obstacles in their way they will be very pragmatic and they will go and find another role. This also relates strongly to whether the sector that you are working in has lots and lots of opportunities, an abundance of alternative options, or whether there are relatively rare opportunities to work on these specific topics. I will talk about the greater ecosystem effect a little bit later in this video.

In terms of attracting talent there are a number of different ways to approach this. In some disciplines a non-public direct word-of-mouth approach with a relatively small number of colleagues, where you say you are looking for someone and you need this skill set, will work. But in a lot of other disciplines, especially large disciplines that are very hot and very topical, it will be a numbers game.

The larger your network is, the more exposure you can get publicly for a role or project that you are recruiting for, the higher the chance that after you have talked to individuals who might be interested and gone through all the filtering in both directions, you end up with sufficient individuals for the roles that you need to fill.

Your reputation both individually and in terms of your group, the alumni from your group and where they have gone, as well as the greater ecosystem in terms of your faculty, the university, and even the country that you are located in will also play a role. Even if you cannot compete directly on things like salary, which is quite a common occurrence in areas of computer science like AI and robotics and computer vision and machine learning, if you have a reputation for a good culture or a wonderful geographic location to work in, sometimes that can tip the balance in your favor even when you cannot necessarily directly compete on conditions or compensation.

Obviously some of these things are long-term cultural changes. They can take years to implement and they are difficult to get right. This is why new early-career academics who are taking their first faculty position often give a lot of thought to the ecosystem and the culture of the group and the university that they are joining, because they know that this will have a critical effect on their ability to retain and recruit talent as well as the overall reputation and prestige of the university.

University roles cannot typically compete or even hope to compete directly with industry salaries and compensation, especially in really hot topic areas. Anything to do with tech, again AI, robotics, machine learning, and so forth. There will often be literally an order of magnitude difference in compensation between a university and an exciting startup or a big tech company.

That said, there are things that you should do and be aware of with respect to salaries. When you are proposing a grant or a fellowship or a project in the first place, do not skimp on the salaries for the researchers you want to recruit. There will be limits to how high you can set the salary, but often people feel like knocking off a few extra percent of the salary is going to massively improve their chances of getting the grant. If they actually get the grant, however, it is going to cause them huge headaches in terms of recruiting and retaining talent.

Almost always in the long term it is better to appropriately cost, and even perhaps slightly generously cost, salaries for your young researchers on your project. If you get the project it is going to make it much easier to attract and importantly to retain that young talent.

In terms of strategy for how you pitch for and apply for projects of various sorts, one of the other things to keep in mind is the type of talent you are realistically going to get. If all of your project proposals are projects where the activity would need geniuses who are very hardworking, very motivated, and very savvy, you are unlikely to be able to recruit all of that talent.

What will probably serve you better is to have a tiered hierarchy of projects and activities that you apply to do. There may be some very ambitious fundamental research projects where you really do need those intellectual powerhouses to have a chance of pulling it off. But you should also pitch some relatively more mundane work where there is very little uncertainty that you can eventually get it done, and where you have a much wider range of options in terms of talent pools from which to recruit.

This also applies to the nature of the work that you are pitching for in your group. If all of your projects are green-fields projects in research areas where you as the experienced supervisor literally have no idea what the eventual solution could be, realistically you are going to struggle with your talent. That talent will inevitably start to falter or struggle on these projects because it is new ground, it is very challenging, and if you are also struggling to provide insightful suggestions and tips it is all going to fall apart.

Again, a hierarchy where there are some projects where you are not really master of it and you do not know exactly what is going to happen, combined with a number of projects where when the going gets tough you can almost certainly provide a very insightful set of suggestions to the talent for how to proceed, is important.

Another key talent consideration when you are recruiting for your projects is the degree of autonomy that that talent possesses. Especially as you scale up the number of projects that you are running in parallel, if you are required to come in and micromanage each of the projects continuously it just will not scale. Eventually you will run out of time and energy.

So both pitching some projects that can run relatively autonomously and finding talent that is able to run for periods of time without extensive detailed input and suggestions from you is key to running a successful lab ecosystem.

I talked earlier about enlarging the pool of talent from which you can recruit by strategically thinking about what topics your projects will cover. To give some specific examples, for those of us who work in robotics or computer vision or artificial intelligence, if we are only targeting computer science graduates that is going to limit our pool substantially, and there is a lot of competition from industry.

If instead you have projects where quite plausibly you could upskill and train a mathematics graduate or an electrical engineer in-house to be quite effective at that project given what is required, that massively enlarges your talent pool. It also means you are competing for talent from pools which may not have as much direct well-compensated industry competition, increasing your chances of finding the talent you need.

Finally, retention should not be overlooked. It is generally easier to try and retain good talent whenever reasonably possible rather than to recruit fresh individuals from scratch to fill roles. While there will be limits to what you can do to keep people happy and engaged, every reasonable effort should be put into this if you have the power to do so. It will save you an immense amount of effort in terms of recruiting, running new advertisements, and doing lots of interviewing.

Retention is just as important, perhaps more important, than recruiting. You will not always be able to retain people. Sometimes it is healthy for all parties for people to move on at some stage, and almost all people will move on eventually unless they become an academic at your own organization. But retention is something that is increasingly important to focus on.

Another part of the retention component is the opportunities, development, and environment that you provide for people in your group or center or institute. All the typical things matter here. Providing professional growth pathways where possible, providing training, and providing a rich work and social environment with opportunities to engage, especially for people coming from overseas and building a new social network, are all important parts of retention.

So the next time you are thinking about a really exciting idea for a project or a fellowship or a grant or a collaboration with industry, also think about the type of talent you would need to do that project. Is it a very limited tiny pool of talent, or is it a very large pool of talent from many different disciplines that could plausibly do the work?

Bake this consideration of talent, talent availability, and competition for talent into your overall due-diligence and development process for all those wonderful research ideas you have floating around.