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
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Candidates are co-supervised by two advisors from two different Max Planck Institutes.
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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.
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A co-advisor from the ELLIS network may be added where it strengthens the project.
Who can be an advisor?
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Advisors are directors or independent research group leaders at a Max Planck Institute, holding W2 or W3 status.
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If a W2 group leader's position is non-permanent, a confirmation (host) letter from the managing director of the institute is required.
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The first and second advisor must be affiliated with two different Max Planck Institutes.
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A co-advisor from the ELLIS network is possible in addition to the main Max Planck advisor.
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Emeriti directors and research group leaders who do not hold a W2 position can act as third advisors.
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:
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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.
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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.
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Hosting: The co-advisor hosts the candidate for at least six months and provides all necessary work equipment.
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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.
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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.
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Intellectual property: IP generated during the project is arranged between the home and the exchange institution.
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Plans: All parties agree on the graduation plan and the exchange timeline set out in the LoI.