We are always looking for talented researchers and engineers who are passionate about (automated) machine learning & meta-learning, recommender systems, information retrieval or some of our other research interests.
To learn about the latest job offers, follow us on Twitter or subscribe to our blog. The latest job offers from our blog are these:
- PostDoc fellowships for ML, AutoML, or RecSys for 2-3 years in Siegen (Germany) and/or anywhere in the world
- 1 x Postdoctoral Researcher or Ph.D. Position in AutoML and/or Recommender Systems
- 2 x Postdoctoral Researcher or Ph.D. Position in AutoML and/or Recommender Systems
Student Jobs (Bachelor / Master)
If you are a Bachelor’s or Master’s student, interested in working with us, please check our dedicated Student section.
Postdoctoral Researcher
Check the top of this page, and our blog for job openings. In case we do not have any openings, we would still be glad to hear from you. Especially, if you have an exciting research idea. For truly outstanding research proposals, we will likely find a way to hire you. Or, we would inform you once we do have an opening. Also, if you are interested in organizing your own funding, have a look at these options:
- The German Academic Exchange Service DAAD, if you are from abroad and would like to work with us in Siegen
- The German Science Foundation DFG, if you are already in Germany (though, sometimes, DFG also has programs to attract foreign talent to come to Germany)
If you are German and interested to work at Trinity College Dublin or the National Institute of Informatics in Tokyo, the DAAD IFI program may be interesting for you, too. Let us know if you are interested, we would be glad to support you in applying and establishing contact.
Please note that we cannot help you with finding a suitable topic for your postdoctoral project. As a (potential) postdoc we expect you to have your own research vision. Please also note, we would only hire a postdoc who has published at least 1 first-author articles at major information retrieval venues (e.g. SIGIR, ECIR), recommender systems venues (ACM RecSys, UMAP), or machine learning conferences or journals (any conference or journal with A or A* ranking).
PhD Positions
Full-Time
Check the top of the page for open Ph.D. positions. However, even if we do not have open Ph.D. positions, we would be glad to hear from you (contact details are at the bottom of this page). Especially, if you have your own research idea, or are interested in an internship. We would also gladly support you if you are interested in applying for a scholarship.
Part-Time / Industry
The University of Siegen is perfectly suited for a part-time PhD, i.e. doing the PhD research besides your normal full-time job. As one of the very few universities in Germany, the University of Siegen offers a cumulative dissertation. This means, instead of writing a few-hundred-pages-long monograph, you need to publish 4 major research articles as the first author (plus an introduction and summary). Those 4 articles should loosely relate to each other, but not as much as if you were writing a monograph.
A cumulative dissertation gives you much more flexibility because you do not have to work on one specific topic over multiple years. Instead, you can have some ‘shift’ in your topic(s). Also, writing up a monograph usually takes months of boring and frustrating work towards the end of your PhD time. Hence, given that you should publish anyway during a Ph.D., there is almost no overhead with a cumulative dissertation, except writing an introduction and a summary, which should not take more than a few days. Also, there is no tuition fee at the University of Siegen, and you do not need to attend any classes. Only if you want to be officially enrolled as a PhD student, there is a fee of 250 Euros or so per semester but this is voluntary. In addition, you can do the entire Ph.D. remotely. However, it would be nice if in the beginning, the middle, and towards the end of your PhD, you would spend a few days in person here in Siegen.
In summary, all you need for a PhD, is to publish four major research articles. Whether this takes 3 years, 5 years or 7 years doesn’t matter.
If you are interested in a part-time Ph.D., we would love to hear from you. But please note that if you want to do a part-time Ph.D., then:
- You must have solid knowledge in the field of your P.hD. project. This means, that when you want us to supervise your Ph.D., you must have a solid knowledge of recommender systems or (automated) machine learning. If you know little about it and are just interested in learning about them, then a Ph.D. is not the right thing for you to do.
- You must have an idea for a specific Ph.D. project. In other words, you must have identified a research problem that you want to solve in the next years as part of your PhD work. This is crucial as we will not provide you with a Ph.D. topic. It is our experience that external part-time students can only succeed if they are truly passionate about their Ph.D. topic. This is rarely the case for a random topic that is given to you. Also, if you don’t have an idea for a topic, then this is a strong indication that you are not really familiar with the field of your intended PhD.
- You must have an original proposal of how to solve that problem. It’s not enough to be aware of a problem (see point 2), you must have an original idea of how to solve it.
- You need to work at a company that supports publishing. This must be evidenced by existing publications of other employees of that company.
- You must have already published at least one paper as the first author at a reasonable conference or journal. It does not need to be a full paper but at least a demo or poster that provides evidence that you are capable of writing research articles.
- Your employer must support your Ph.D. This means, your employer must allow you to work at least one day per week on your Ph.D or your work itself must be directly research-oriented. A Ph.D. cannot be done only on weekends!
Visiting PhD Students
Contact us, if you would like to work with us for a few months in Siegen. We are always open to self-funded visitors and the DAAD has several programs that may support you.
General Advice on Doing a PhD
A good PhD Topic
A good Ph.D. topic is key to the success of your work. This means, you must have a) identified a specific problem, and b) a plausible idea of how you could solve this problem. Something like “I want to use machine learning to improve abc” is not a suitable Ph.D. topic. Just throwing dozens of machine learning algorithms to a problem and see what algorithm solves the problem best, is not a sufficient Ph.D. contribution. It is important, that your proposed solution is novel, and convincing (ideally other persons familiar with the problem would say “Oh yes, of course, why haven’t I thought of that?).
Expertise
Doing a PhD is not about obtaining broad knowledge in a field such as machine learning or natural language processing. A PhD is about deepening your existing knowledge and, most importantly, creating new knowledge. “New knowledge” in terms of creating a novel algorithm, designing a new method or metric, …. This means, to start a PhD, you should have already good knowledge in the broader field (e.g. machine learning) and ideally some knowledge in the special field of your PhD (e.g. recurrent neural networks). If that is not the case, you might be better off to do first some online courses e.g. in machine learning; or do a Bachelor / Master (by research) in that field.
Positions at the NII in Tokyo, Japan
We work closely with the National Institute of Informatics (NII) in Tokyo, Japan. If you are interested in working at the NII, have a look at the programmes of the Japan Society for the Promotion of Science. They offer scholarships for foreigners at all career levels, including senior researchers, to conduct research visits in Japan for up to two years. Permanent positions at the NII are advertised on NII’s website. If you are from Germany, the DAAD may have additional programs to fund research visit. As a PhD student, the DAAD may fund you for up to six months, as a postdoctoral researcher up to 2 years.
Contact Us
If you would like to work with us, we would love to hear from you. Please send us a message with the following information.
Everyone (Intern, Visitor, Ph.D., PostDoc…)
- Your current employer/university:
- Current place of residence:
- a) Earliest b) Prefered c) Latest possible start date:
- Min/Max/Pref. Duration of your stay [if applicable]:
- How do you wish to fund your stay [if applicable]?
- Your experience in Machine Learning:
- Your experience in Recommender Systems and Information Retrieval:
- Your experience in AutoML, algorithm selection, optimization, meta-learning, and NAS:
- Your Work/Industry Experience:
- Any notable contributions to software projects e.g. on GitHub?
- Any noteworthy awards?
- Your Motivation / Why do you want to join our group?
- Anything else you would like to tell us about yourself?
- Your questions for us:
(Prospective) Visiting Bachelor/Master Students or Interns Only
- Do you have any publications already (e.g. have you published your Bachelor thesis)?
- In what percentage do you rank among your fellow students (e.g. Top 1%; Top 5%; Top 10%; Top 20%; …):
- How good are your math skills?
- How good are your programming skills?
(Prospective) Ph.D. Students Only
- Type of Ph.D. (Full-Time; Part-Time; Visiting)
- Have you already published? If yes, please provide details:
- Your Google Scholar profile if existent:
- What’s the final grade of your Master’s degree?
- In what percentage do you rank among your graduation class (e.g. Top 1%; Top 5%; Top 10%; Top 20%; …):
- How good are your math skills?
- How good are your programming skills?
- If you are interested in a part-time Ph.D., please briefly explain how your employer will support you:
- If you have a specific idea for a project please let us know [optional]:
(Prospective) Postdocs Only
- Your Google Scholar profile:
- Your Top-3 publications in the past 3 years (URLs to full text, please do not attach the publications):
- Your two most successful student supervisions (Bachelor/Master or Ph.D. students):
- Acquired Funding:
- Teaching Experience:
- Your research vision or project proposal (3-5 paragraphs):
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