Co-Advising Guidelines

In the Max Planck Artificial Intelligence Network (MP-AIX), every doctoral researcher and postdoc is jointly supervised by two advisors who bridge artificial intelligence and a domain science. These guidelines summarise who can act as an advisor and the commitments that advisors and candidates accept when they join the network.

The advising tandem

  • Candidates are co-supervised by two advisors from two different Max Planck Institutes.

  • One advisor works in a field close to machine learning / AI, the other in an application area ("X")​ — together forming an AI + X (or X + AI) tandem.

  • A co-advisor from the ELLIS network may be added where it strengthens the project.

 

Who can be an advisor?

  • Advisors are directors or independent research group leaders at a Max Planck Institute, holding W2 or W3 status.

  • If a W2 group leader's position is non-permanent, a confirmation (host) letter from the managing director of the institute is required.

  • The first and second advisor must be affiliated with two different Max Planck Institutes.​

  • A co-advisor from the ELLIS network is possible in addition to the two Max Planck advisors.

  • If an emeritus director acts as first or second advisor, a third advisor must be added.

 

Commitments of the advising tandem and the candidate

By completing the Admission Form and signing the Letter of Intent (LoI)​, the primary advisor, the co-advisor(s) and the candidate agree to the MP-AIX terms:

  • Funding:​ The advisors secure funding for the candidate for a minimum of three years overall. Within MP-AIX, 50 % of the personnel costs are co-funded centrally; the remaining 50 % is provided by the advisors' institutes.

  • Time split:​ The candidate spends at least 50 % of their time with the main advisor and visits the co-advisor for a minimum of six months. The partitioning of this time is flexible.

  • Hosting:​ The co-advisor hosts the candidate for at least six months and provides all necessary work equipment.

  • Same location:​ If the second advisor is based at the same university/city, the parties meet regularly with the candidate, who is encouraged to spend at least one month abroad during the project.

  • Publishing:​ Results are expected to be published in top-tier venues in machine-learning-driven fields and/or in the co-advisor's associated interdisciplinary field.

  • Intellectual property:​ IP generated during the project is arranged between the home and the exchange institution.

  • Plans:​ All parties agree on the graduation plan and the exchange timeline set out in the LoI.