The Aalto RSE hiring process
This post describes the hiring process of Aalto RSE. The goal is to make hiring more equitable by providing the background information so that everyone can apply successfully. For those not applying to us, it might still provide some valuable insight about how to market your skills as a PhD making a sideways career move. What’s said here may not apply to every organization, but it might give you some things to think about.
Disclaimer: This page is a rough average description of the past, not a promise to always do this in the future.
Aalto RSE has usually hired people who have postdoc experience and will transition to a more applied software/data/computing oriented role (as opposed to being focused on writing papers). For many people, we are the first experience of job applications post-degree and thus people have to learn how to present their skills in a new, non-academic context.
One should start by reading about us - we have lots of information publicly available about what we do and how we think. This should be understood in order to do the next steps well.
The cover letter
The cover letter is the most important thing we read, and the first and most important filter. It’s read before the CV.
At the level we are at, almost everyone’s CV and achievements are effectively equivalent. Does it matter who got the most fancy papers? Who has the most awards? The classes people took? When most of a person’s knowledge has come from self-study, probably not. The cover letter is the chance to interpret your skills in the context of the job you are applying for.
When reading the cover letter, the first question we ask is “does this person know what they are applying to and know why they think they are a good fit?” (It’s always interesting to get letters which clearly don’t understand the job, but on the other hand it’s an easy filter.) The first paragraph should answer this question and that the rest of the letter will go into detail about why. Start with the most important information, don’t make it hard for us.
Beyond that, talk about interests and skills as relevant to the organization. Discuss special projects, including non-academic ones or random things that you are interested in (this is especially true for us, since we are the transition from academia to practical work). Our job advertisement gives you some specific ideas that you can talk about. Anything specifically important to the job should be pointed out here and not just left in the CV.
If you don’t exactly fit the stated job requirements: here is the chance to explain it. The job requirement has to say roughly what we need (to not waste people’s time when applying, and because our hiring decisions must be justifiable based on the requirements), but there are many cases where someone with a different experience can accomplish our actual goal (as said in the job ad or found in your background research). A person that can say this, that they are adaptable, and will have a very good chance.
We have adopted some system of anonymous recruiting. We request that cover letters are submitted without identifying information (name, signature, etc) so that one person gives them numbers, and a broader group tries to take a non-biased look at them. After this initial impression, we bring in the rest of the application. Don’t make assumptions about what the reader will know about your background, just say it.
The letter should be as short as possible to get the information across. One page is usually about the shortest we get, and a bit less than two pages is typical. But if it’s engaging, we’ll read as much as you write. Remember, most important information first, don’t make us hunt for things.
The rest of the job application
The CV serves as non-anonymous reference information, but they are hard to read and all look pretty similar. To be honest, we don’t worry that much about the format and contents here: get us basic factual information in the most efficient way. For our particular jobs, non-academic skills such as software/data tools are more important than scientific articles, etc. Remember, we are busy and have plenty of applications, make it easy to read.
Open Science isn’t just good for research, it’s good for you, too. If you can point to public repositories of work you have done, this is very useful. Things like Gitlab/Github profiles with activity and your own projects, links to data you have released, etc. They don’t have to be perfect - something is better than nothing. The best case would be a few projects which are well-done (and you know it and point them out to us), and plenty more stuff that may be of lower quality to show you can get simple stuff done simply. Not everyone is fortunate to have a field where they can practice open science throughout their career, but even publishing a project or two before they apply for a job with us is very useful.
Despite what the previous section said, we do try to dig through applications that seem on-topic but don’t say everything we are looking for, to give them the most fair shot we can.
The filtering process
We always need to heavily filter the list down. Some relevant filtering includes:
Do they know what job they are applying for? Can they connect their skills to the job?
Have they touched on the main points in our job advertisement and the linked “Become a RSE” page?
Are they interested in teaching, mentoring, and real collaborative projects? Do they know what kind of teaching and mentoring we do?
Is there enough knowledge about the research process?
Any relevant skills about this call’s particular topic (if there is any)?
How do their skills and experience match what our team is currently missing, regardless of the open call?
How similar has their previous work been to “research engineering” (helping the research process) instead of only focusing on academic promotion?
The recruitment team makes several passes over and we discuss how to filter down. We try to get a good variety of candidates.
Sometimes, there is some initial recorded “video interviews”, which provide some initial familiarity in both directions before the actual interviews. We know these are non-interactive and a recording isn’t a conversation so this is harder than an interview, but we consider that when watching them. One shouldn’t worry too much about these, if we do them.
Our actual interviews are not designed to be stressful. We have some prepared questions and go through them in a friendly manner. You have a chance to ask questions to use at the beginning and end (and any other time too). The questions are designed to hear about your experiences and not trick or test you.
We don’t currently ask technical challenge questions. The number of things which you’d need to know is so broad, it’s more important that you can learn things quickly. Since we usually interview relatively advanced people, we can instead look at existing projects they have done and check references, without having to do a technical challenge. This may change depending on the type of candidates we are interviewing, but just like the main interviews we are more interested in how people think, rather than raw knowledge.
In the future, there might be more “meet the team” kind of events.
We want to respond to people as soon as possible, but there’s a simple fact: we don’t want to tell anyone “no” until we are very sure we have an acceptance (we don’t want to tell someone “no” and then hire them later), and we have very many qualified candidates. So there is often an unfortunately long delay in hearing back. We hope that everyone knows within a month, though (and ideally ~2 weeks if all goes well).
If you don’t make it
We get a relatively large number of applications, with a lot of good people. So far (before 2023), we have been hiring at a relatively high level - researchers with postdoc experience who have been some sort of RSE-like experience with helping others with research (beyond only focusing on making papers for themselves) and technology. Don’t let this discourage you. There are many qualified applications, so if you don’t get selected, that doesn’t mean that you were unqualified. We look at everyone, regardless of their level, for every position. The fit to our particular job is more important that anything else, so keep trying until you get the right fit - it’s just a numbers game.
Old job application text
For reference, this is an older job application text, so that you can see how the things above are integrated. (to be updated with the 2023 version soon)
RSE job advertisement, 2022
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Aalto Scientific Computing is looking for a
Research Software Engineer/Supporter
To a permanent, full-time position.
Are you more of a programmer than your researcher colleagues? Are you more of a researcher than commercial developers? Do you fit in both, but have a home in neither? Be a Research Software Engineer with us and find your home. If you are looking for a career path which combines the interesting parts of both fields, this is a good choice.
Aalto Scientific Computing is an elite “special forces” unit of Research IT, providing high-performance computing hardware, management, research support, teaching, and training. Our team consists of a core of PhD staff working with top researchers throughout the university. Our services are used by every school at Aalto University and known throughout Finland and the Nordics. All our work is open-source by default and we take an active part in worldwide projects.
In this position, you will:
Provide software development and consulting as a service, depending on demand from research groups.
Provide one-on-one research support from a software, programming, Linux, data, and infrastructure perspective: short-term projects helping researchers with specific tasks, so that the researchers gain competence to work independently.
As needed and depending on interest, teaching and other research infrastructure support.
Continually learn new skills as part of our team.
Primary qualifications: There are two main tracks, and candidates of diverse backgrounds are encouraged to apply – every candidate will be evaluated according to their own unique experiences.
PhD degree with research experience in some computational field and much knowledge of practical computing strategies for research, or
Software developer or computational scientist with a strong software/open source/Linux background, scientific computing experience, and some experience in research. Masters degree or similar experience.
This particular call emphasizes the ability to work in machine learning and AI environments. The ideal candidate will be working closely with machine learning researchers, and thus a background in machine learning is highly desirable.
Ability to tackle any problem with a researcher’s mindset and a developer’s passion for technology.
Experience or knowledge of the principles of open source software, open science, and software development tools such as version control.
Please see https://scicomp.aalto.fi/rse/become-a-rse/ for more information on what kind of skills we value - or more precisely what you are likely to learn.
What we offer:
You will join the dynamic Aalto Scientific Computing team, where you will learn from some of the best research IT specialists in Finland.
Co-working within top-quality research groups, getting experience in a wide variety of fields and developing an extensive network of scientific contacts. This includes contacts to the Aalto startup scene and community.
A way to be close to the research process while focusing on interesting computational problems and not the publication process.
Our program will offer you a chance to improve your software skills – you are expected to engage in plenty of professional development.
Open Source is our expectation. All (or most) of your code may be open source and may be added to your public CV, depending on the needs of researchers.
Salary will be according to experience, for a recently graduated PhD similar to a postdoc salary. Work hours are flexible, but are expected to sync with the audience being served. Primary workplace is Otaniemi, Espoo (Helsinki region), Finland. Aalto University has a hybrid work policy which allows 60% remote work possibility, and our team takes good advantage of this flexibility.
To apply successfully:
Please include a separate cover letter (~1-2 pages). Please try to write your cover letter avoiding information like name, gender, nationality or other demographic information that is not directly related to why you would be the right person for this position (this includes, for example, a signature on the letter) unless you think it benefits you. This will assist in anonymous recruitment possibilities. The letter should include for example:
Why being a Research Software Engineer is for you,
past research experience, if any
past technical teaching or mentoring experience,
past software development experience (even informal self-learning),
past Linux, command line, or scripting experience,
highlight one (or a few) collaborative projects you have taken part in and your role within it, and
what you bring and what you intend to learn.
A normal professional or academic CV including
a list of your technical and programming tools and level of proficiency (e.g. basic/proficient/expert). This is the time to show the breadth of your experience.
Github link or other public sample code. If not available, whatever is possible to demonstrate past programming experience. Please highlight one or two of your outstanding research software projects.
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