For RSE candidates and community¶
We occasionally hire people. To get notified (of this and other similar jobs):
If you are looking for jobs inside and outside of Aalto, consider following the Society-RSE job vacancies form.
If you are inside of Aalto, join the RSE community mailing list (mailing list). This will get announcements of both our jobs, events, and other research groups looking to hire a RSE skillset.
This page is designed to guide people into the interesting world of research software engineering: providing a view into the types of skills that are useful to research groups at Aalto. It also provides links to training material which our RSEs should learn after starting (so don’t be intimidated by what you see on here!).
Do you like coding and research, but don’t want an academic career path with publications as your sole purpose? Be a Research Software Engineer with us! Our pilot is designed to bridge the gap between academic research and a future career in research software or a research scientist in a company.
If (some of) the following apply to you, you are a good candidate:
I like the academic environment, but don’t want to focus just on making publications.
I am reasonably good at some programming concepts, and am eager to learn more. I know one language well, can shell script, and generally familiar with Linux.
I am interested in going to a scientist-developer kind of role in a company, but need more experience before I can make the transition.
General qualifications and duties¶
We strongly prefer good computational researchers (PhD level preferred) who can improve their software development skills than the other way around. This role can be combined with other roles, but note that this is not targeted to those who intend to follow a tenure-track academic career path. New RSEs will get a training period which rounds out any missing skills. They will also be involved in a complete support package: they will have the chance to be involved in teaching an infrastructure development.
From time to time, job advertisements are posted on the Aalto University job portal, with notices on various other channels including Aalto scientific computing mailing lists.
What you do¶
At least at Aalto, 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 desired, teach and provide other research support.
A typical cycle involves evaluating potential client researchers, meeting, formulating a work plan, co-working to develop a solution, teaching and mentoring for skill development, and follow-up.
All will be done as part of a team to round out skills and continuous internal knowledge-sharing.
You may also be interested in these presentations on the topic of “what we do”:
Below, we have a large list of the types of technologies which are valued by our researchers and useful to our RSEs. No one person is expected to know everything, but we will hire a variety of people to cover many of the things you see here.
Most important is do you want to learn things from this list? Can you do so mostly independently but with the help of a great team?
General tech skills¶
Our broad background on which we build:
Basic mandatory skills include Linux, shell scripting, some low-level programming language (C, Fortran), and programming in several more languages (Python particularly advantageous).
Good knowledge of computer clusters, batch systems, and high-performance computing.
Any additional programming, workflow, research, or system tools are a plus. You should have a wide range of skills, but the exact skills are not so important. Most important is sufficient fluency to pick up anything quickly. These skills should be listed as an appendix to the cover letter if not included in the CV.
Advanced parallel programming skills are a plus, but equally important is the ability to create good, simple, practical tools.
Git, GitHub, git-based collaborative workflows.
Software testing, CI, documentation, reproducible, portability, etc.
But at the same time, we don’t just want people from purely computational backgrounds. You’ll work with people from experimental sciences, digital humanities, etc, and good people from these backgrounds are important, too.
A good attitude towards mentoring and teaching and an ability to explain complex subjects in an accessible way.
Commitment to diversity and equality of researchers among many different backgrounds.
Good knowledge of English. Finnish is advantageous but not required, our internal working language is English.
Teaching and mentoring skills¶
You won’t be just preforming technical tasks. As part of being a RSE, you need to help others to be self-sufficient as well. This requires teaching and mentoring skills.
This is a selection of advanced skills which are useful (remember, this is what you might learn, not what you already know):
Advanced experience of debugging/profiling/developing Linux tools, including Git, Intel and GNU compiler suits and corresponding tools.
Software building tools like Make, CMake and alike.
Advanced knowledge of parallel programming models, experience of parallel programming (OpenMP, MPI).
Advanced GPU computing / programming (CUDA, OpenACC, OpenMP models), experience of porting software to GPUs.
Profiling and optimization - both of low-level languages and high-level.
Knowledge of scientific software and packages including Matlab, Mathematica, Python libs, others is beneficial.
Experimental data collection, LabView, etc.
Workflow automation, shell scripting, porting from single machines to clusters.
Docker, Singularity, containers.
Data analysis tools like R, Python, pandas, numpy, etc. are beneficial.
Julia, Matlab, Mathematica.
Web development, cloud operations.
Scientific Computing on other operating systems.
Open science and data¶
As a RSE, you should also serve as an advocate for open science, reproducible research, and data management.
Data management, data engineering, data wrangling.
Open source software development, community formation.
Software packaging and distribution, (e.g. PyPI, conda, etc.).