IST Austria

Computer Vision and
Machine Learning Group


Advice for Applicants

Dear prospective applicant, please read the section of this page that best fits your situation as well as the FAQ at the bottom, which answers many of the most common questions. Afterwards, feel free to contact me by email. I do read all incoming email, even if I don't necessarily reply to all of it. To prevent your email ending up in the spam filter, include the code "67867776" in your subject line. If you include this code I will know that you read this page. If not, there's a good chance you'll get an automated reply or none at all.


External Applicants (i.e. you're not at IST Austria already)


Prospective Interns

We do not have opportunities for summer internships in 2017. We really don't.

Prospective Master Students

IST Austria does not offer Master degrees. If you're a Master student elsewhere and the rules of your home institution allow for it, it might be possible to work on a master thesis topic over the course of an internship in our group. If this is what you would like to do, please see the Prospective Interns section.

Prospective PhD Students

Our institute has a structured PhD program following the model of the US research research universities. Admissions are possible with either a Bachelors or Masters degree (or equivalent) and the language of the program is English. The admissions to this program are handled centrally by the IST Austria graduate school. The application deadline is typically every year in January, interviews are in February/March, offers are sent out in March/April, and the program starts in September.
If you plan on applying, you do not have to send me an email first but can go directory to the Applications page. Feel free to express your interest for computer vision and machine learning in your application and/or list me as a potential supervisor. You will not need my permission for that. Once you have been accepted into the PhD program, feel free to contact me to discuss opportunities in my group and research topics, please see the section for internal applicants below.

Prospective Postdocs

There are usually some postdoc positions available in my group, both in Machine Learning and in Computer Vision. The topics are not fixed but agreed on mutually. Therefore, you should have a clear idea what kind research questions interest you before applying. Candidates must have a strong track record in the respective field, proven by publications at first-tier conferences and journals: CVPR, ICCV, ECCV, IJCV, PAMI for Computer Vision; ICML, NIPS, JMLR, ML for Machine Learning. It also helps if I have heard about your research before, so feel free to talk to me at conferences or workshops. If you do not fulfill these criteria, e.g. because you plan on switching fields, feel free to apply anyway, but be aware that you will need convincing arguments why you think you would be able to make significant contributions to computer vision or machine learning in the future, and why you think my group specifically is the right one for this effort.

Prospective Faculty

IST Austria is growing and in the process we are constantly looking for new faculty in all subject areas (CS, Math, Life Sciences, etc.), either as Tenure-Track Assistant Professor or as Tenured Professor. For Assistant Professors there is an annual call every December, but applying outside of the cycle is possible in exceptional cases. Applications as Professors can be sent any time. If you would like to know more about IST Austria before applying, feel free to contact me.

Prospective Visitors

We can host faculty from other institutions for short or long reseach visits, including sabbaticals. Slots are limited, however, and the principle of excellency applies here as well. If I haven't heard about your work, I might not be the right host for you. Otherwise, feel free to contact me.


Internal Applicants (i.e. you are at IST already or at least have an offer)


Prospective Rotation Students

I do take rotation students every year, and if your background and interests are at least remotely related to Computer Science, Math and/or Data Analysis, you can be pretty safe that I will accept you for a rotation (so far I never had to refuse). There is no fixed list of possible rotation topics, each topic is designed individually based on the student's background and the group's current research topics. If you are interested in a rotation, simply drop by my office (main building, third floor) and ask. Sending me email is also possible, of course, but most likely my reply will be that we should just meet and talk about the possibilities.

Prospective PhD Students

Since you got accepted to the PhD program, there is a good chance that I already know about you and your interest to join my group. Feel free to contact me again anyway after you have been accepted, so we can make more concrete plans together. Generally, I expect my students to have solid background in the following topics. If you lack any of these or feel uncertain, the first year of gradschool is a good time to catch up.

  • Math: Linear algebra, multi-dimensional calculus, probabilities
  • CS: Programming skills in Python, ideally already some experience with tensorflow
  • Other: Fluency in English, working knowledge of LATEX
To fulfill your credit requirement, I would recommend that you pick courses from the following modules:
  • Track Core Courses: "Data Science and Scientific Computation (DSSC)", but taking "Computer Science (CS)" won't hurt either
  • DSSC/Probabilistic Models: e.g. "Statistical Machine Learning" (cross-listed with CS/Artificial Intelligence)
  • DSSC/Data Analysis: e.g. "Methods of Data Analysis"
  • DSSC/Optimization: e.g. "Convex Optimization"
  • CS/Artificial Intelligence: e.g. "Project Course: Computer Vision&Machine Learning" (cross-listed with CS/Visual Computing)
  • CS/Visual Computing: e.g. "Image Processing"
Courses from other modules, including from the Physics, Maths, Biology or Neuroscience track can also be useful. This will depend on the specific research topic.


Frequently Asked Questions


  • Q: Will you be accepting new PhD students for the year 20xx?
  • A: Almost certainly yes. Generally, I look on average for one new students per year, but I also happily take more if more excellent candidates apply.

  • Q: What criteria will I have to fulfill to be accepted as a PhD student?
  • A: Our graduate school makes decisions taking a large number of criteria into account. For me personally, most important are
    • the quality of the university where you studied,
    • your grades in relevant courses (e.g. linear algebra, probability...),
    • your prior experience with the topics related to our research,
    • your statement of purpose,
    • the letters of recommendation.
    Note: I do not care much about prior publications, except if these are at the absolute top conferences/journals in the field (ICML, NIPS, CVPR, ICCV, ECCV, JMLR, TPAMI, IJCV).

  • Q: I am a PhD student elsewhere. Would you be willing to be my co-supervisor / join my thesis committee / act a referee for my thesis?
  • A: This depends very much on the individual case. Please send me an email (and don't forgot the special code).

  • Q: Do your interns/students/postdocs get paid?
  • A: Yes, all interns, graduate students and postdocs at IST Austria receive full-time working contracts, including a salary, insurance, vacation days, etc. It is also possible and very welcome to apply if you have external funding, and if accepted you will have the same benefits as IST employees.

  • Q: If I join your group as a PhD student, who will be my direct supervisor?
  • A: Me. I keep the group small enough such that I can supervise all students myself.

  • Q: What is it like to be a part of your research group?
  • A: My group members will be able to answer that more objectively.

  • Q: What sort of problems are you working on?
  • Q: One part of our group works on statistical machine learning (theory and algorithms), and one part works on computer vision (algorithms and models for visual scene understanding). Both parts are connected through an overall interest in problems of transfer learning and learning with weak supervision. See our research page for details. The list of topics is broader for co-supervised projects, including then, e.g., applications of machine learning in the life sciences.

  • Q: Can I work on Deep Learning when joining your group.
  • A: Deep Learning is not a core topic of our research, but topics that include Deep Learning are possible, especially for computer vision projects.

  • Q: Could you write me a letter of recommendation?
  • A: That depends:
    • if we have not met: no (sorry, no exceptions)
    • if we have met but not collaborated on scientific questions: most likely not, but there could be exception for non-scientific issues (e.g. visa/green card issues)
    • if we have collaborated on scientific questions: most likely yes, but please contact me first


Thanks to Hal Daumé III for inspiring part of the contents of this page. Last updated in 2017.