Finding a perfect PhD is somewhat like dating: there is no such thing as a soulmate-PhD, but some are still better than others; the number of options seems overwhelming at first, but most of them crumble once inspected carefully; and, of course, once committed, the choice will significantly influence the rest of your life. To make it even more challenging, the soulmate-PhD problem is also expected to be dealt with at the most vulnerable point in the lifetime of a student—as if by Murphy’s law, the deadlines usually land somewhere between the final in the sequence of many exams and the Masters thesis defense. Under such conditions, even the most genuinely motivated students might be at risk of falling into the trap of uncertainty and marrying a PhD that does not fully capture their interests and expectations.
This blogpost is meant to serve as a roadmap to your perfect PhD. It will push you to reflect on your intentions and research interests, introduce a simple framework for tracking your progress, suggest several common search engines for PhD vacancies, and walk you through the general process of writing applications and preparing for interviews. It is mostly comprised of personal experiences and insights, with occasional references to useful tools and resources. Importantly, the process described here primarily applies to graduate schools and PhD positions in (Western) Europe and in life/social sciences (primarily cognitive science and neurosciences); while steps 0–4 should be widely relevant, steps 4–8 might diverge for PhD applications in other academic systems or fields.
Shiny is a powerful tool in R for you to show off your work to the world, without explaining all the complicated code behind your analysis. Because of its free and open-source development and deployment structure, sharing your methods or work online was never easier. For example, in our recent publication in the Journal of European Psychology Students my colleagues and me used Shiny to implement a network method in which we used the concept of network centrality to determine the most relevant articles in a research field. Because I believe there are a lot of benefits in sharing one’s methods, my hopes are that this blog post has the possibility to also inspire you to share your own work through Shiny. I will walk you though developing your own R Shiny application from scratch, tailoring it to your design choices, and publishing it online, in 7 easy steps. Continue reading
Investigating concepts associated with psychology requires an indefinite amount of reading. Hence, good literature reviews are an inevitably needed part of providing the modern scientists with a broad spectrum of knowledge. In order to help, this blog post will introduce you to the basics of literature reviews and explain a specific methodological approach towards writing one, known as the systematic literature review. Continue reading
A hackathon is an event, typically lasting for 24-48 hours, in which a group of people with diverse backgrounds come together to solve a problem by building a first working prototype of a solution (usually a web app, program or a utility).
There is something inherently likable, or dare I say, smart, about hackathons. They have a specific goal, your progress and results are measurable, getting a first working prototype is both achievable and realistic, and it will all be over in 24-48 hours. I have come to appreciate hackathons a lot over the last five months where I’ve participated in five, and won two of them with my teams. I would like to invite you to participate in one as well by giving you 7±2 tips to make your hackathon experience especially enjoyable. Continue reading
With a reliable internet connection comes access to the enormous World Wide Web. Being so large, we rely on tools like Google to search and filter all this information. Additional filters can be found in sites like Wikipedia, offering a library style access to curated knowledge, but it too is enormous. In more recent years, open online courses has rapidly become a highly popular method of gaining easy access to curated, high quality, as well as pre-packaged knowledge. A particularly popular variety is the Massive Open Online Course, or MOOC, which are found on platforms like Coursera and edX. The promise – global and free access to high quality education – has often been applauded. Some have heralded the age of the MOOC as the death of campus based teaching. Others are more critical, often citing the high drop-out rates as a sign of failure, or argue that MOOCs do not or cannot foster ‘real’ learning (e.g., Zemsky, 2014; Pope, 2014). Continue reading
Programming is a skill that all psychology students should learn. I can think of so many reasons on why, including automating boring stuff, and practicing problem solving skills through learning to code and programming. In this post I will focus on two more immediate ways that may be relevant for a Psychology student, particularly during data collection and data analysis. For a more elaborated discussion on the topic read the post on my personal blog: Every Psychologist Should Learn Programming.
Here is what we will do in this post:
- Basic Python by example (i.e., a t-test for paired samples)
- Program a Flanker task using the Python library Expyriment
- Visualise and analyse data Continue reading
Do you wish to publish your work but don’t know how to get started? We asked some of our student authors, Janne Hellerup Nielsen, Dimitar Karadzhov, and Noelle Sammon, to share their experience of getting published. Continue reading
Bayesian statistics is what all the cool kids are talking about these days. Upon closer inspection, this does not come as a surprise. In contrast to classical statistics, Bayesian inference is principled, coherent, unbiased, and addresses an important question in science: in which of my hypothesis should I believe in, and how strongly, given the collected data? Continue reading
If you have gone through the trouble of picking up a copy of the Publication Manual of the American Psychological Association (APA, 2010), I’m sure your first reaction was similar to mine: “Ugh! 272 pages of boredom.” Do people actually read this monster? I don’t know. I don’t think so. I know I haven’t read every last bit of it. You may be relieved to hear that your reaction resonates with some of the critique that has been voiced by senior researchers in Psychology, such as Henry L. Roediger III (2004). But let’s face it: APA style is not going anywhere. It is one of the major style regimes in academia and is used in many fields other than Psychology, including medical and other public health journals. And to be fair, standardizing academic documents is not a bad idea. It helps readers to efficiently access the desired information. It helps authors by making the journal’s expectations regarding style explicit, and it helps reviewers to concentrate on the content of a manuscript. Most importantly, the guidelines set a standard that is accepted by a large number of outlets. Imagine a world in which you had to familiarize yourself with a different style every time you chose a new outlet for your scholarly work. Continue reading