Turn AI into Discovery Across the Sciences

The Max Planck Artificial Intelligence Network (MP-AIX) empowers doctoral researchers by linking them with advisors across the Max Planck Society to develop and apply AI methods in every scientific discipline.

The Max Planck Society conducts basic research in the natural sciences, life sciences, and humanities, covering a broad range of research fields from Astronomy & Astrophysics to Biology & Medicine, Computer Science & Robotics, Material Sciences & Technology, Chemistry & Physics, as well as Environment & Climate or Arts and Law. With its 84 Max Planck Institutes and cutting-edge facilities, it is the international flagship for fundamental research in Germany.

The MP-AIX program supports excellent young researchers by connecting them to advisors across the Max Planck Society (MPS) to carry out research on the development and application of AI methods. Each student is matched with two advisors at different institutes:

  • one advisor working in a field close to ML and AI, and
  • the other advisor in an application area (“X”).

Each junior scientist supported by the program will form the core of a concrete collaboration between two different research fields. Students split their time across the two sites, with the constraint that at least 6 months are spent in each place.

These MPS “AI+X” Ph.D.s conduct cutting-edge curiosity-driven research in machine learning and inference pertaining to scientific applications across the whole research spectrum represented in the MPS. 

Advisors can be both MPS PIs, i.e. directors or independent research group leaders, or co-advise with PIs from the ELLIS Network.

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What makes MP-AIX distinctive

  • Co-advising across institutes — joint supervision by two advisors from two different Max Planck Institutes, bridging AI and a domain science.

  • Shared funding — 50 % of personnel costs are co-funded centrally, 50 % by the advisors' institutes, for a minimum of three years.

  • Mobility — candidates spend time with both advisors, with a research stay of at least six months at the co-advisor's institute.

  • A network — a cohort, a kick-off workshop, shared compute and joint training across the MPG.

 

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