 yes okay thanks and yeah see you see you later after the next break bye so next up is let me write it in hackmd so the the notes okay we will do this all week so the next part is called humans of scientific computing and the idea here is that we've had like all these courses have always been talking about the technical properties of what we're doing like how how you how we run stuff and the computers and so on but we rarely talk about us and we're the ones that you see and are helping and it can be a good example to let you know about how we got here and how we know how to support you and maybe even give you some inspiration for your careers so yeah um you can be asking questions down here um there's no slides or anything for this I just have some questions prepared and it will basically be me interviewing Temu here so Temu is a research software engineer who started with us last year about nine months ago or so something like that after the summer and yeah well let's start off so Temu can you tell me a little bit about your background yeah uh I I'm originally from Aalto I did my studies in Aalto so I started in 2005 and the year is kind of relevant a bit later because uh and my studies were signal processing and machine learning and and later on data science more generally um so so my studies were not were not software that that is I think the main point here so I did programming but I I did into software and then I I graduated I did my PhD also in Aalto and I graduated in 2016 okay um yeah so then once you got your PhD how did you start off your career yeah so I guess after yes after the PhD and after you do your PhD you usually are kicked out from the university and of course that is what happened to me as well so I did two postdoc periods or or like six years as a postdoc researcher and what I did was I was working for a national library and and then in a well well the point is that I was working uh with within like digital humanities and and digital social sciences projects research projects so basically you were the computer person yes I was the computer guy or the data guy and and then what happens is happens very naturally or very naturally to me is that you you realize that you are actually uh you are actually more your role is more about helping the other researchers who don't have a really like a technical background uh so you are helping them with their data so so scraping data collecting data processing data and making it into a format that the other people can other people can uh process and do their research so it's more about like facilitating other people's jobs than and then then at some point I realized that I haven't actually done any research in many years because of all my working hours for like helping others so and that's yeah yeah exactly and that's that's how we come to this uh to this present that that I I actually really like that role but it's I was still a researcher so there's this conflict that you're supposed to be writing articles and making making like studies but then you're you don't really do that so is it fair to say you weren't a researcher like I guess like were your names on the papers like I mean I guess all the project that happened just couldn't have happened without you so yeah if we believe in collaboration how can you not be a researcher there I mean actually I know the answer which is that academia has the rewards are all mixed up so yeah but like that's a good question that like I'm my researcher when I'm actually making like facilitating the group and and nothing happens without your input but then kind of like this is still you're not the one like making the questions or but anyway so so the next step was that this this all the position this research software engineer position came up and uh and so I came here and now I'm in the support role like doing doing very much what I was doing already but now I'm not a researcher anymore I'm the like support person personally I consider us researchers even though okay our wouldn't consider us I mean okay yeah just have a different role in the process and by the way one one important thing that I I thought that at simo and thomas and enrico and you and me we are all all these basically these research software engineers in in alto so so we are the people especially simo and I guess yeah especially simo is the one people like making the hbc clusters happen and then then if you need if if all the people need help then we are the guys who can who are there to help out we've been mentioning this term research software engineer and I haven't given a proper introduction to it yet so what does research software engineer mean no well you know you you want me to answer that you know that there's no good answer and then then like like yeah like so it's unfair to throw that ball to me okay yes yes please do because you have you have so rehearsing so it was a term invented about 10 years ago to represent people who are in the research process but their goal is to work with software and data and make research possible instead of being solely focused on writing the papers and coming up with ideas and this is something that we've started at alto for some time now and we have the service available where us research software engineers can basically come and ask you like we you can ask us and we can come and help your work with our specialties so you can focus on your articles and science and ideas and so on and not have the computer get in your way and I think you'll hear more about this as time goes on in the course but yeah maybe someone can put a link to the rse page in here since we're talking about it in the hack of the in the notes um let's see so in research what like what have you learned from your research jobs that helps you know that you're working for us here like has that time been wasted or was it important for what you do now uh as as uh uh no it it wasn't wasted and especially I think there are two things here the first thing is that it is very good for us in our support role to actually no research and know how research is done and know how researchers work so I that is definitely one positive thing because uh if somebody comes to do this role from purely an industry background for example then it might be um kind of surprising that what are the workflows for academic researchers for example uh in in good in good and bad for example that the timetables are very lively and and there are long periods of time of time when seemingly seemingly nothing is happening but then you have a conference deadline and then suddenly like like uh the world is on fire that everything is like needs to be done like immediately but then the second the second second thing is that uh when I started to started to kind of like listen to other people and what are they their requirements what kind of data they need how how they need the data to be processed and also like communicating these things that what is actually what can be done and in what timetable then I was then I started to learn this software side because in my own studies and in my own research I I didn't I was doing programming I was doing algorithms I was doing data but I didn't actually know the software practices and so then I was I started to learn them yeah so and and that is that is of course very useful were you worried about making this transition like when you first saw this as a possibility to come work for us did you were you anxious or anything yeah I I think my my main point of anxiety was that uh because I hadn't had any any formal education or I didn't have like uh basically like self-taught so so that are there a lot of things that I don't know that I don't know are they like unknown unknowns that that I get that I get like I get like steamrolled with stuff that I I didn't know even existed but but then it turns out that that kind of like all of us are in a sense like self-taught and and also that nobody knows everything and even now when uh when people come to us the researchers and and they have a project or or they have a problem most often is just that let's start thinking about it together and let's try to solve the problem and you don't have it always works out somehow yeah it somehow works out and and like people yeah it's it's important to important to have an open mind and yeah and try so okay I've got so the follow-up question so what do you know now that you wish someone had told you or taught you when you started your career and you get to choose at what point this is yeah I I think um I think the like software development practices like how to how to use version control how to use um how to use environments like efficiently virtual environments and and and how to which those were the things that I started doing very very late in my research research of career and I hope that like I would have been smart enough to start using them right away because those are like software development practices uh but but they are not meant to be kind of a burden because they actually make things a lot easier for you in the long run yeah so uh and these are these are things that like this this uh research software engineers can help researchers for example now so we can we can help people so that they don't repeat our mistakes yeah uh there's a question for me in the notes what motivates you to make a transition to data science I guess this is for me specifically so so people know my background was in computational chemistry and chemical physics that kind of stuff and the transition to data science I mean it sort of happened gradually like I started doing more and more data related things and actually there was one point where okay during my phd I moved a little bit that way and then for my postdoc I realized getting experience in a completely different field would probably be good for my career so I went somewhere where the work was much more data sciencey and I think it's good I mean this is the interdisciplinary kind of stuff that we care about I mean not that computational or not that computational physics is that far from data science compared to other things but okay so what would you say to someone who might be interested in careers outside tenure track like someone in academia but might be interested in things that are not just tenure track or do you have any thoughts there uh yeah it's it's really hard to it's really hard to say there's just it's just difficult to be a phd student or a researcher because it's it's really tough because like you're always applying for money and always always having this kind of like one year plan or two year plan and so so yeah I I don't think I'm in a in a good position to give any advice to anyone okay we can we can give like emotional support in our research yeah yeah so I guess there's two final questions and we're almost out of time so it is what do you hope to continue learning and what comes next in your career have you thought anymore yeah at the at the moment I'm I'm really content with the with this RSC job I really like helping people so I think I'm for now I'm very content to just be here and and like learn learn new stuff that relates to this because there's always like every day something new to learn because the tools are just going forward in such a fast manner that yeah okay so that that is what is mixed yeah so um I guess now we can do a quick hack and deq and a but we can also continue this during the break asynchronously um so there's a question do I need to apply for funding now and then so I am working on getting funding for the research software engineer service itself but it's not like my personal funding so it's like you know individually we have our jobs we're secure and we have a future and we're working together to ensure the team's future which is a much different thing than everyone's contract only lasting two years and everyone just expects to have to be gone sometime so it's a much different kind of applying for funding and also I mean our funding is basically secure from the school of science so we aren't we don't have to keep renewed like doing things on a short term and we actually can take a long term view which is really important there's a good question there what are these key skills and technologies required for research software engineer it's actually someone put up this link here to code refinery dot org and this is a thing which we are part of um alto's part of and it runs workshops twice a year and I would basically say it's like the rsc basics course kind of thing it talks about version control software testing documentation things like that and if you attend that workshop you'll be set on a good path and we can try to comment a little bit more during the break um any final comments or anything yeah I wanted to say one thing about what demo said that was really good so about like learning of the new tools and what the future holds uh in that like throughout the whole whole like whenever you're starting what whatever point you are in your like uh computational journey or like learning using these tools or whatever it's going to be always this kind of a thing that there's always going to be new tools there's always going to be new things and you feel at some point you will feel lost in all of these things and everybody else has more shiny tools than you have and like your your stuff is crap and everybody else is crappy stuff so you you get this feeling that like uh something uh like maybe you you don't know about some stuff and that happens to everyone that happens to us as well so so don't be discouraged so so I would say that like there are always going to be new tools because stuff is moving forward like the uh the the tools are moving forward and we constantly have to really re uh in invigorate ourselves and find find new things to use and and we evaluate what is what is actually now like what is now required yes and so so so it's it's always good to remember that like throughout this course there will be a lot of new concepts throughout your research progress there will be a lot of new things to learn don't be discouraged by it because everybody's like going to like encounter the same things so so that will happen like it will happen to you it will happen to everybody nobody will know about new things or understand new things when they first encounter them and about the like stuff that you can already learn it's it's always good idea to go where somebody has like already plowed the the road for you so the code refinery and places like that are very good places to learn what somebody else has learned to work basically to learn from people who who already have like good practices and and we do that as well like when we encounter somebody who has a nice thing we try to incorporate it into our workflows because uh like yeah why why use bad tools when they're good available but not everybody like you cannot know them before you encounter them so it's always good idea to to keep like uh keep on the lookout and find this stuff but i think yeah maybe it's time for a break i just wanted to add this good addition yeah okay so i think we should get to the break soon so as you may see here there's a another poll so you can answer is the course good okay needs improvement too fast too slow good topics vote for all that apply with the o's like we did at the start so with that said i guess our break extends until five past hour so see you later and do keep asking the questions okay bye