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Programme

The Geo.X Young AI Academy – Generative AI for Earth System and Planetary Science offers a structured 10-month programme for doctoral and postdoctoral researchers from Geo.X institutions. The programme supports participants in moving from occasional use of generative AI tools to a structured and responsible integration into their scientific workflows.

Through the Academy, you will develop

  • Core competence in GAI, effective communication with GAI and automation for research tasks
  • The ability to reflect and decide when GAI usage is appropriate and when not
  • The ability to critically evaluate AI-generated outputs and their appropriate use
  • The capacity for ethical, lawful, and responsible AI use in the academic context
  • A peer network across Geo.X institutions for continued exchange and collaboration

These core competences, which we want to develop, are inspired by and follow the AI Fluency “4Ds” framework (delegation, discernment, diligence, description). 

At the end, you will leave the Academy with

  • A documented, research-aligned (G)AI integration roadmap (your “what I do / what I don’t do / why” for your own workflow)
  • An evaluated small-group project connected to your research, with documented outputs (e.g., workflows, white papers, or publication-oriented material)
  • A certificate of participation upon successful completion

  • To run small dissemination/peer-learning activities in their institutions

Why we offer the Academy 

Generative AI is rapidly becoming part of scientific work. But how can it be used responsibly, effectively, and with real benefit to research? This Academy is designed not just to introduce tools, but to strengthen your capacity to make informed, strategic, and responsible decisions about generative AI in your research.

How the 10 months are structured

In our 10-month cohort (2×5-month modules) programme, we support doctoral and postdoctoral researchers in moving from ad hoc GAI tool use to a personal, structured, and research-aligned integration. The courses are focusing on no-coding practices and are largely tool agnostic, so you can use the tools available to you or acquire access yourself, depending on your needs. 

Module 1 — Generative AI for Scientific Workflows

Foundations + practice: how GAI works, limitations, ethical implications, practical integration into scientific workflows via AI assistants, tools, and agents, and critical usage and evaluation of AI outputs. This module comprises four one-day in-person courses, bi-weekly online check-ins, and selected expert talks.

In-person events 
In-person events will take place in Berlin or Potsdam and are expected to run from 09:00 to 16:30. We strongly encourage you to attend all in-person sessions to get the most out of the programme. If unavoidable conflicts arise, we will share the key materials and takeaways.

Community check-ins
Community check-ins are regular peer-exchange sessions designed to support collaboration and reflection. Participants discuss their progress, share use cases, explore tools, exchange feedback, and present what they have developed.

Module 2 — Advanced (G)AI Applications in Research

We conduct expert-guided small-group projects connected to your research. Module 2 stays intentionally open: we develop topics and subgroup projects together during Module 1, so the second Module reflects what the cohort actually needs. This module comprises expert input for subprojects, bi-weekly online check-ins, and a farewell event including project presentations. We also encourage and support you in sharing your knowledge in your working group and institute.