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Archive for April, 2017

What’s working in a think tank actually like?

By uczjsdd, on 21 April 2017

ParakilasJacobCrop_0Dr Jacob Parakilas has a PhD in International Relations, and is now Assistant Head of the US and Americas Programme at Chatham House, an international affairs think tank. Jacob contributed to our Careers in Government and Policy forum for researchers in February. For those who couldn’t make it in February, Jacob also kindly agreed to give us an insight into his career path, below.
 

How did you move from academia to your current role?

I moved straight from my PhD programme into policy work, first at an NGO and then to Chatham House. It was always basically my intention to go back into the policy world; academia wasn’t really the goal for me. I’d previously worked in think tanks and government in Washington, DC, so I had some lower-level experience in the field and good sense that it was where I wanted to be.

When I started applying for jobs in think tanks towards the end of my PhD programme, I heavily emphasised my research background, since it was what I was currently working on (and excited about). After a string of rejections, I re-focused my applications and balanced out my research background with my professional skills, which made all the difference in terms of being taken seriously.

What does a normal working day look like for you?

It depends enormously on the time of year, what’s happening in the world, and a variety of other factors. As a whole, my job involves roughly equal measures of fundraising, administration, management, research and public-facing work, but the balance isn’t consistent year-round. During the US elections, I spent a lot of time on public-facing work (TV and radio appearances, giving lectures, being on panels, etc.); at the end of financial years I tend to spend more time on management and fundraising activities. It’s almost never the case that my day involves just one category, so I’m rarely if ever bored.

What are the best things about working in your role?

We have a pretty direct line to policymakers – when we put out a piece of research, we can generally get it in front of relevant policymakers relatively easily. We also tend to be the first point of call for media when they need analysis on political developments, which means we have opportunities to speak to a much wider audience on a regular basis. Finally, my subject area means that I get to work on an amazingly broad range of topics – everything from US defence strategy to trade agreements to the potential role of artificial intelligence in geopolitics.

 
What are the biggest challenges?

We face a fairly constant pressure to fundraise to support our work. My institution is funded from a broad range of sources, which is the right approach for all sorts of reasons. But it also means that we have to develop and maintain relationships with corporations, governments, foundations and individuals – all of which require slightly different approaches, and which requires significant time commitments.

It can also be difficult to balance long-term, strategic goals against the need to respond to daily events. That’s been especially true in my role over the last few months, since things have been moving so quickly and unpredictably in US politics & foreign policy.

Is a PhD essential in your work?

Not absolutely essential but very useful. Many junior think tank researchers don’t have doctorates, and in mid-career research posts/middle management it’s a mixture of people with and without them. At the highest levels – research directors, directors of studies, institute directors – it’s much closer to universal.

The research skills are largely transferrable, though the style of writing is more different than you might think (I wrote a very policy-oriented PhD and it still took more than a year before people stopped telling me my writing was ‘too academic’). The biggest transferrable skills are fundraising, time management and project management, which all look a bit different inside and outside academia but rely on the same fundamentals. Finally, it’s not the biggest consideration, but having a PhD is also a helpful mark of credibility when you’re dealing with senior figures.

What’s the progression like?

Think tanks tend to be pretty flat hierarchies, which is good in terms of getting opportunities to do a range of different types of work, but less good in terms of offering a clear, predictable path upwards. On the plus side, they tend to be extremely well-connected, so from a think tank it’s pretty easy to make the jump to government, the private sector, self-employment as an independent consultant/researcher, or to NGOs. There are some examples of people who start out at the first rung of the think tank ladder and climb straight up to heading a programme or institute, but most people move up through the various sectors adjacent to think tanks. In other words, it gives you a lot of options.

What top tips would you pass on to researchers interested in this type of work?

Talk to people! On the whole people, in this sector are friendly and open to polite requests for informational interviews. It also gets you on their radar, which helps when it comes to applying for jobs or finding consulting opportunities.

I can’t stress the importance of administrative skills enough. A large portion of my average day isn’t directly research-related (despite the fact that I’m a researcher). That’s true throughout the think tank world: almost no one has a pure research job, so you have to be able to capable of doing a whole range of work – and to show that in your applications.

A PhD’s experience in Healthcare Data Science

By uczjsdd, on 10 April 2017

MaheenAs part of her PhD, Maheen Faisal undertook a three month placement at uMotif, a digital healthcare company. This type of hands-on work experience is great for career exploration, and Maheen learned lots about herself and the industry. She’s kindly agreed to share her experience, below, so you can learn from it too!

My background is in Mathematics – I have a BSc Mathematics degree and an MSc Applied Mathematics degree. Data Science was a field that I was always interested in exploring but the context never seemed very interesting to me. When I came across a Data Science role in a healthcare company, it was almost like a fusion of two things I was quite interested in and decided to go with the placement.

My placement was at uMotif which is a digital healthcare company that provides a patient data capture platform in the form of a mobile phone app. In 2016, uMotif launched a global study “100 For Parkinson’s” where people with Parkinson’s disease and without tracked their health on their smartphone for 100 days. This resulted in the generation of a large complex dataset consisting of over 2.2 million data points and 4218 participants.

My role at uMotif was that of a Data Scientist and it involved using advanced statistical analysis techniques and machine learning to analyse the 100 For Parkinson’s dataset and to explore hidden patterns in the data. Various questions were posed by uMotif to use the dataset to a) understand the Parkinson’s population better and to discover potential digital biomarkers of Parkinson’s and b) to utilize the dataset to understand how uMotif as a company could improve participant/patient retention in future studies.

Towards the end of my placement, I had the chance to convert a complex network graph into a powerful and engaging info graphic for the 100 For Parkinson’s end of study press release: http://umotif.com/news/the-dataset-from-100-for-parkinson-s-exceeds-2-2-million-data-points. This was quite fun and rewarding, to have a physical outcome of my work that was shared with the participants of the study.

I gained a lot of experience working with “Big Data”. The first thing I learned was MySQL which is a database management system, in order to be able to query the data that I needed to work with. I completed a Machine Learning course to grasp the basics of Machine Learning. I then learned how to use the Machine Learning and Statistics toolbox in Matlab, R and the Amazon Web Services Machine Learning console. I also learned how to use Tableau – a brilliant data visualization software program, which helps visualize complex data.

Honestly, at times the work placement felt extremely challenging and I felt as though I would not be able to accomplish much or meet the expectations of my placement supervisors. Persevering through it however, I learned that I sometimes underestimate myself and can actually pick up difficult concepts quickly and meet expectations.

When thinking about whether the placement influenced my career decision I would say yes and no. Previously, I was pretty sure that I would stay in academia as I quite enjoy research. I also wasn’t sure whether there was anything out there for me that I would actually enjoy. At the moment I’m still not sure whether I would like to stay in academia or not, but I do know that if I ventured out, that Data Science is a field that I would enjoy working in.

Top Tips for other researchers?

  1. Make sure you sit down and think about where exactly you would like to work or what you would like to do. It may not be immediately clear so start with something really basic and build from that. For example, if I had not gone down my current career path, I would probably be a doctor or be working in healthcare in some capacity. With that in mind, when I was brainstorming for my PIPS, I tried to look for healthcare related roles until I found something that interested me.
  2. Don’t be shy when contacting companies, the worst that can happen is that they won’t reply. I got my work placement by sending a message through a generic “Contact Us” form on the company website!