ELLIS PhD & Postdoc Program

The ELLIS PhD & Postdoc Program supports excellent young researchers by connecting them to leading researchers across Europe and offering a variety of networking and training activities, including summer schools and workshops. ELLIS PhDs and postdocs conduct cutting-edge curiosity-driven research in machine learning or a related research area with the goal of publishing in top-tier conferences in the field.

See a list of our current ELLIS PhDs and postdocs here!

There are three tracks within the ELLIS PhD & Postdoc Program: the academic track , the industry track, and the interdisciplinary track. These tracks have separate requirements for admission and criteria for activity during the appointment, but otherwise offer the same benefits, network and resources to the applicant.

Academic track

PhD students and postdocs in the academic track strive for international collaboration as they partner with two European academic institutions in their research. These candidates are supervised by two advisors from different European countries: one of the advisors must be an ELLIS fellow/scholar or unit faculty; the other advisor should be an ELLIS fellow, scholar, unit faculty or member. PhDs and postdocs in the program visit the exchange institution for min. 6 months (the partitioning of this time is flexible).

Industry track

The industry track is open to PhD and postdoc candidates that will be part of a collaboration between an academic institution and an industry partner, and will spend time conducting research at the industry partner during their PhD or postdoc. The candidate will spend a minimum of 50% of their time at the academic institution, and at least 6 months (cumulative) with the industry partner.

For this track, both advisors may be located in the same country. One advisor will represent the academic institution and the other the industry partner. One advisor must be an ELLIS fellow/scholar or unit faculty. The second advisor can be an ELLIS fellow, scholar, member, unit faculty OR it is also possible for the second advisor to join if they have co-authored a paper with the applying student as a result of their collaboration, in a top-tier venue in machine learning or related sub-fields (details here). ELLIS Amsterdam is proud to have the most industry track students of the ELLIS network, thanks to our widespread collaborations with industry through partnerships such as the Bosch-Delta and QUVA labs.

Interdisciplinary track

The interdisciplinary track supports PhD students and postdocs aiming to foster collaborations in two different research fields, one of which is not traditionally associated with machine learning/AI (e.g., law, biology, social sciences & humanities). The candidates will spend a minimum of 50% of their time with their main advisor (an ELLIS fellow/scholar) and at least 6 months (flexible partitioning) with the second advisor whose main expertise is unrelated to machine-learning/AI. This second advisor should further hold a tenured faculty position within their research field (if they are not an ELLIS fellow/scholar themselves).

Both advisors are based in Europe (or associated countries with ELLIS units, e.g. Israel) and may be located in the same institution/city. If that is the case, no 6-month visit is required but the PhD student/postdoc should regularly meet with their second advisor. Additionally, the candidate is then encouraged to spend at least a month abroad during their thesis/postdoc.

Who can apply? (Current PhDs or postdocs)

ELLIS fellows, scholars or unit faculty may nominate PhD students or postdocs who are working with them to become ELLIS PhD students or postdocs in the academic or industry track. Note that postdocs of either track are currently only recruited via nomination. Please see here for more details about the requirements and the nomination process.

*It is now possible for industry representatives to join the ELLIS PhD & Postdoc program as Industry Track advisors if they are not ELLIS Members, if they have already published a first-author paper together with the applying student candidate in a top-tier publication in machine learning or related sub-fields (see ellis.eu/members for a list of accepted publications).