This funding is used to establish a postdoctoral program in Complexity Research and Data Expertise at the CSH (CSH PP), including training and career development of a pool of data experts at different postdoc levels. The program aims to employ and retain highly qualified researchers at the CSH in Austria, equipping them with the skills to drive digital transformation at an internationally leading level and systematically use big data to understand complex systems.

Within the CSH PostDoc program, early-career scientists will develop data-driven, multidimensional analysis methods and models in order to identify tipping points, explore the possibilities of alternative transformative developments, and evaluate them in scenarios. Innovative methods will allow the analysis of system and network resilience – including climate and environment, cities, economy, circular economy, supply chains and trade, transport and mobility, energy industry, democratic decision-making, innovation systems, and social interaction – to quantify, monitor and, ideally, optimize outcomes, while participatively identifying and addressing potential unintended consequences.

Available, long-term and consistent large datasets from all areas play a key role here. The procurement and preparation of data often requires more time than the actual scientific data analysis. Researchers will gain skills in data curation, stewardship, and governance to facilitate data collection, cleaning, integration, and utilization as well as the merging of different datasets. They will also be trained in setting up metadata repositories, data catalogs, and data rooms to ensure data quality, accessibility, and long-term value. The overall aim here is to improve data quality and massively increase the knowledge gained from the data.

Postdoctoral researchers will be actively involved in CSH research projects to familiarize themselves with data owners, partners, and stakeholders, and to understand their needs and requirements. At the same time, postdocs should establish themselves as internationally leading scientists through publications in leading scientific journals, as well as through broadly effective communication of their research questions and results as trustworthy experts for policymakers and the public. To acquire the necessary competencies, postdocs will receive training from CSH staff in the following areas:

1. Data curation (approx. 60% of the training):
   Organization and integration of data collected from various sources. In the CSH PP, this includes strategies and expertise for the procurement, preparation, and maintenance of data, as well as data security, annotation, publication, and presentation. The goal is to ensure that the value of the data is preserved over time and remains available for reuse and storage. Furthermore, the program teaches postdocs the skills to add value to data.

2. Science communication (approx. 20% of the training):
   Effective communication is essential to ensure that research has impact beyond the scientific community. Postdocs will therefore learn to communicate with users, data owners, and the public in order to highlight the importance of research and data science, while also counteracting skepticism toward science. Special attention is given to communication via social media and to developing skills in the visualization of research results. In addition, postdocs will acquire the ability to pass on these communication skills to others, for example through dedicated workshops.

3. Tech ethics and digital humanism (approx. 5% of the training):
   Raising awareness of the opportunities and risks of digitalization, big data analysis, and the use of artificial intelligence (AI) to ensure that people benefit equally from research results.

4. Research funding expertise (approx. 5% of the training):
   Acquiring skills to secure funding for their own research and working groups.

5. Leadership (approx. 5% of the training):
   Developing skills to effectively lead and manage their own research groups.

6. Project management (approx. 5% of the training):
   Planning, organizing, and executing research projects efficiently.