Digital Innovation School FAQ


My background is in ________. Can I apply?

Yes, in our Graduate Program, we welcome students from any academic background. We work with a range of universities to find a graduate curriculum that fits with each student’s experience and interests. Please note that we expect students to have foundational quantitative skills (for example, probability theory, regression analysis, descriptive statistics) and comfort with a programming language (e.g. Python, R, Julia, C++, Mathematica, Matlab), database query language (e.g. SQL), and/or statistical software (e.g. SPSS, SAS, Stata).

Yes, if you will have received your degree when you begin the Graduate Program in Complexity Science, you are welcome to apply in the current call. Please contact us at if you expect a more substantial delay.

This is not encouraged unless you have a significant amount of full-time research experience after your Bachelor’s degree. These expectations are intended to meet the admissions requirements of our university partners and to ensure students are well-prepared for the demands of independent research that are required for the PhD. Students who have not completed a Master’s or who do not have an equivalent level of experience will often be required to complete additional coursework when enrolling in their university, which can lead to substantial delays in progress toward the PhD.


This is neither necessary nor encouraged. While it is expected that applicants will learn about the research happening at the Complexity Science Hub in the process of preparing their application, and thereby will identify some potential thesis advisors or collaborators from among the Digital Innovation School faculty, the final round of interviews will include time for students and faculty members to discuss project ideas and mentorship possibilities. In the application stage, we are looking for applicants who are interested in diverse theories, approaches, and methods by which to address the questions and problems that are important to them and thus may have connections to several researchers in the faculty. A candidate will not have an advantage in the selection process by having an existing connection to a Digital Innovation School faculty member.

Your vision letter should describe the question or problem that you are interested in with sufficient specificity that the Admissions Committee gains an understanding of a discrete, tractable step you might take toward addressing this question or problem, including some possible methodologies you might use. The vision letter should include references to Complexity Science Hub projects that provide a framework or context for your interests; and/or publications (from CSH or elsewhere) that illustrate the type of research approach that appeals to you and presents a possible means by which to address the question or problem of interest; and/or examples of your past research or academic experiences that have influenced your interests and goals for your PhD. It is important that your vision letter explains specifically why the research environment of the Digital Innovation School and the approaches of complexity science are ideally suited to what you want to accomplish – both during your PhD and in the longer term in your future professional career.

You may request that up to three letters of recommendation be sent to Our first-round eligibility check will eliminate any third letters that do not add significant new information about the applicant.

Yes, please encourage the people providing letters on your behalf to send those to as soon as possible. There is no need to wait until your application is complete.

No, once students are offered a position in the Digital Innovation School, we will help them enroll in the appropriate university. Students are assured admission to a university when they join the Graduate Program in Complexity Science.

Yes, we anticipate one call every year through 2030. The current plan is to have one admissions cycle per year, but we will consider additional calls as we learn more about our potential applicants.

For students who want to join the program in 2025 or later, applications will be due in the preceding December (e.g. to start in September-October 2027, you will apply in December 2026). We do not plan to offer rolling admissions.


In 2024, we hope to have all offers made by the end of July. Applicants should learn before the end of June if they are being invited to interview.

The Digital Innovation School uses a three-stage review process. Following an eligibility check, in stage 1, the application materials will be reviewed by the Admissions Committee to assess the alignment of the applicant’s background and interests with the research at the Complexity Science Hub, and the applicant’s potential for independent and rigorous scholarship in the area of complexity science. In stage 2, short-listed applicants will be invited to interview with a panel of Complexity Science Hub researchers according to a prescribed format wherein the candidate will present a research study and respond to questions to understand their critical thinking and scientific understanding. In stage 3, finalist candidates will present themselves and their ideas to a broad group of Digital Innovation School members in order to learn more about their interests and goals for the PhD. Applicants who are invited to participate in stage 2 and stage 3 will be provided detailed instructions on the process and the expectations.

We will consider requests for deferral on a case-by-case basis.

Choosing an Advisor / Choosing a University

Applicants should spend some time reviewing DIS faculty and their research interests, recent projects and publications, and areas of expertise in the process of applying. During the interview process, applicants and prospective advisors will have a chance to learn more about each other both during applicants’ presentations and in individual meetings to be arranged for the finalist candidates. The university co-advisor, if different from the primary advisor, will be determined once the student has identified their primary advisor.

No, the Complexity Science Hub is a non-profit research institute and is not accredited as a degree-granting university. We partner with 8 universities in and around Vienna that together comprise the Digital Innovation School and those universities bestow the PhD or Doctor degree. Students in the Graduate Program in Complexity Science complete coursework and thesis-related requirements of their degrees according to the guidelines set by both the Digital Innovation School and their university.

During the interview process, applicants will receive information about university programs that align with their backgrounds and interests. Applicants are welcome to specify a preference for a particular program but should note that it is not always possible to match each student to their preference based on limits to available resources and capacity. A formal offer to join the Graduate Program in Complexity Science will include the proposed university affiliation.

Progress Toward the Degree

That depends on the program of study you will pursue. The Digital Innovation School is unique in offering students a range of disciplinary specializations to accompany their training in complexity science. All students will complete courses in data structures and management, analytics and statistics, mathematical and/or computational modeling, open science / responsible research practices, and data ethics – along with graduate seminars and peer discussions. All students will complete a series of complexity science-focused modules and “master classes” within the Digital Innovation School. Students will complement this core with university courses that are specific to their interests and field of study. Students can expect to take approximately 8–14 classes, depending on the various ECTS points, program specifications, and learning goals.

Students must complete all of their university requirements, including the necessary coursework, exams, progress reporting, and research products, including but not limited to a written dissertation describing the thesis research and defense of the thesis to a committee of experts. Permission to write and defend the thesis is given by the Thesis Advisory Committee and must include the explicit approval of the advisor. The Digital Innovation School expects students will have three first-author manuscripts that will make up their thesis.

Yes, the publication expectations are achievable. Publications in the applicable areas of complexity, network, and data science and adjacent fields tend to be more bounded than publications in some areas of e.g. social sciences and economics and thus can be completed in a shorter time. Keep in mind that exceptions can be made in exceptional circumstances. The publication expectation is meant to put students in a strong position for future opportunities.

Publications reflect a series of projects that together make up the doctoral thesis. In general, the projects – and papers – can be thought of as follows: paper/project 1 is a relatively straight-forward extension of previous work in a direct and tractable way; paper/project 2 evolves from project 1 as an interesting “future direction”; and paper/project 3 is the opportunity to pursue a new direction. The projects are not necessarily sequential but they should build from each other and always benefit from your advisor’s guidance and expertise.

Because of the time needed for internships, the Graduate Program in Complexity Science is prepared to support students who need more than three years to complete their doctoral studies. As long as students have demonstrated satisfactory progress towards the degree – as determined by the completion of university and Digital Innovation School requirements, annual Thesis Advisory Committee meetings, and regular discussions with their advisor – an extension can be granted. All contract extensions depend on the availability of funds.

Other considerations

Yes, students in the Digital Innovation School receive a fixed gross salary of EUR 37557 per year, paid in 14 parts. Based on this salary, the net income (what you receive in your bank account after taxes and withholdings) for a single person is approximately EUR 1967 per pay period. Students receive this salary in exchange for 30 hours per week of work on your thesis research. The remaining 10 hours per week is unpaid time to be spent on coursework and other degree requirements.

Yes, there are several national and international fellowships that are appropriate to students in the Digital Innovation School. We suggest interested students apply once they have begun their thesis research at the Complexity Science Hub, around the time they submit their thesis proposal / exposé, during their first year of studies. The DIS team will support students who wish to submit applications.

Generally part-time work is not possible while one is enrolled in the Graduate Program in Complexity Systems, as the DIS salary is in exchange for 30 hours per week of work on the thesis research – and the remaining 10 hours per week is needed for coursework and other degree requirements. If there is a part-time position that is definitely less than 10 hours per week and it would not interfere with the thesis research and other obligations, an exception can be considered.

If you wish to retain your current employment – either part-time or full-time – while conducting thesis research under the guidance of a Complexity Science Hub researcher but are not seeking a salary or stipend from the Complexity Science Hub, you are welcome to contact us at to discuss possibilities.

No, the program requires residency in Austria and regular presence at the Complexity Science Hub and the affiliated university. Students are eligible for research visits or internships at other sites, but such absences are only permissible within the context of Digital Innovation School research and training activities.

No, the working language of the Complexity Science Hub is English and graduate-level coursework at our partner universities is conducted in English. Vienna is an international city and English is widely spoken. Nonetheless, German courses are available at the Complexity Science Hub for students who would like to learn or improve.

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