Welcome to the NERDS side! 🤓
We are always interested in working with motivated and dedicated students and have plenty of interesting opportunities for Master and Bachelor theses. If you are interested in doing a project with us please follow the 4 steps below.
1) Before you contact us: Are we a match? 💘
Our general expertise best fits the Data Science study programs, but we are happy to supervise students from all study programs if the topic makes sense. Make sure to explore the full list of computer science advisors at ITU before approaching us – someone else might be a better fit for you: https://wiki.itu.dk/computerscience/index.php/Supervisors_for_projects_and_theses
We strongly prefer to supervise groups of 2 or 3 students.
🚨🚨🚨 Before you approach us, make sure the following know-how exists in your group:
- 10 must-know statistical concepts
- Data visualization basics
- Python or R programming
- If you plan to work with networks: Networks basics (pdf)
If you do not already have this foundational know-how before starting with the research project we will almost surely have to decline supervising your group. In that case you will need to consider other supervisors or find a group member who has the required skills. We developed this policy after having supervised students who thought they could learn these skills on the fly. Narrator: They could not, and we all had a bad time.
If you have this know-how: Congratulations, we are a potential match! 💘
2) BSc. and MSc. Student projects
Have a look at our currently proposed projects, last update 2022-08-30:
Or have a look at our personal project pages:
Or feel free to come up with your own topic. Have a look at our members and our research to get inspired and to find the right supervisor for you:
3) What we expect from you, what you can expect from us
- We provide dedicated supervision with regular meetings
- We guide you as best as we can but expect you to be proactive and communicate issues early
- We provide a social space including an initial meeting between all our students. Socialize with your peers – they are an important resource!
- We provide work/meeting space: Slack, and physical space/tables
- We encourage you to take part in our regular seminars with guest speakers
- If we see the potential and dedication for it from your side, we are happy to develop projects together into scientific papers
4) Contact us
After you have read and understood all of the above and want to do a project with us, contact us here: https://forms.gle/bdSWHqMSiAZJHuwv8
We will get automatically notified and will get back to you as soon as we can – it could take a few days. It is possible that even if our interests are a perfect match we just do not have the capacity to supervise anymore students.
How should I write my thesis? Are there some standards I should follow?
Yes. Please read these two helpful posts about writing a thesis. We will expect you to uphold the standards described there:
Further, we suggest you use the following ITU LaTeX template: https://github.itu.dk/bapl/itu_thesis_template
How should I structure my thesis presentation?
Start with the research question and a quick summary: What is it that you want to answer, why is that important, and how are you doing it? Then you can more or less follow the thesis structure: background (how does it connect to what others have done), what data/methods did you use and why, what is the result, conclusion. One slide before the conclusion is usually good to discuss limitations and outlook (what were you not able to do and why, and what else one could do in the future). When you say what you did, try to connect with the literature of the field. For example “Here I followed the algorithm/method of [this or that book/paper].” If you did something new it is good to say that explicitly.
Should I present something in my thesis presentation on top of what I covered in the thesis?
No, please don’t do this. Stick to the thesis, nothing else. We have seen students doing this and it made their presentation considerably worse.
What do you recommend to read when I start my PhD?
- Lessons from my PhD: https://web.eecs.utk.edu/~azh/blog/lessonsfrommyphd.html
- The Good Research Code Handbook: https://goodresearch.dev/
- Writing Science by Joshua Schimel (Amazon link, or ask Michael to borrow the book)
- The Craft of Scientific Presentations by Michael Alley, with: Slides, Checklist [pdf]. Videos: https://www.assertion-evidence.com/