Summer School for Systems Modeling

In this summer school, IIASA provides systematic guidance on the development and use of mathematical and computer models, addressing uncertainties in data and processes, exploring solution spaces, and distilling viable options for taking policy action. Our goal is to equip you with a solid understanding of modeling practices and limitations of models.

The two-week course is designed for Master’s and PhD students, as well as post-doctoral researchers who wish to use or develop models broadly related to the sustainability agenda. It is open to newcomers but also to those who have already been exposed to modeling and would like to add depth to their experience. It is also open to systems researchers who would like to gain a better understanding of the available tools. Many examples we will discuss are taken from IIASA’s portfolio of tools and methods, ranging from ecological models, socioeconomic systems, to integrated assessment tools of energy, air, water, biodiversity, and food.

The objective of the summer school

Real-world systems models that support change are the result of the successful coalescence of many different stakeholders, each coming to the table with their own priorities, agendas, training, skillsets, constraints, resources, and perspectives. Few things are more challenging or more rewarding than when a team of drastically different participants can come together and successfully make the transition from each asserting “we should do something” to collectively agreeing “this is a thing we can and should do together.”

Our goal in this summer school is to provide a guided experience and practice in achieving this type of collaborative, team-science systems modeling. While graduate programs and other existing schools focus on how to make effective and efficient progress on pre-defined research questions, assembling teams with the needed skills and experiences, instead we focus on the real-world challenge of negotiating among stakeholders to define and advance research questions that serve everyone’s interests well (and therefore have a stronger chance of gaining broad support to act on the results of the models produced).

Our participants will spend the first week in short courses on a variety of topics, but will then be guided through a process of self-organization into project teams of their own creation. The second week will focus on the mentored experience of having to work in these emergent, diverse teams to make progress towards shared goals. Participants will navigate the challenges that come from having team-members with different training, cultures, priorities, and skill-levels, and will gain experience in how systems modeling can act as a powerful tool for collaboration in addition to being a method for advancing scientific insight. The school concludes with a round of presentations by participants.

After this course, you will not only be able to design and implement models, but also to critically assess modeling approaches of others. To benefit most from this course, you should feel comfortable with quantitative methods, including differential equations, optimization, and basic probability calculus, as well as with reading and writing simple code (e.g. in Python or R). In the selection process your specific academic field is less important to us than your enthusiasm, curiosity, and willingness to work in international and interdisciplinary teams.

The course will be taught by experienced scientists from IIASA and partner organizations who have ample experience in developing and applying models to real-world problems.

Application information