PhD Project Description
You will work on methods for sustainable large-scale system modelling and tooling, partially within the context of a large European project OpenSCALING involving large companies such as Bosch, Volvo Trucks and Saab and universities from Germany, Hungary and Sweden. The goal of the project is to enable development of more efficient systems in different sectors such as aviation, automotive and building to meet climate targets set by the EU. This requires an approach buit on open standards, and simulation tools need be enhanced to better support large-scale systems and distributed controllers optimized to minimize energy consumption and greenhouse gas emissions.
Within the context of this project, for this doctoral work the focus will be on developing tool-support for large scale system modeling using the equation-based object oriented Modelica language with some machine learning extensions, development in the open source OpenModelica framework, targeting model quality, sustainability analysis with visualization of simulation results for different design decisions.
You will be working in tight collaboration with our industrial partners, to understand and identify common needs and will be collaborating with academic and industrial partners on the extension of current standards (FMI, SSP, Modelica).
Relevant links:
- ITEA project page: OpenSCALING
- Modeling and simulation tool developed at LiU: OpenModelica
Required Qualifications
For general qualifications, see the CUGS announcement of the PhD student positions. For this project, the candidate should have the ability of understanding and developing complex software. The ability is a necessary to tackle Large-Scale Cyber-Physical System Model-Based Development. Additional qualifications for this project:
- Knowledge in software engineering, and general development/management tools for software projects is needed
- Strong communication skills in English, both verbally and written
- A PhD student’s work is driven by curiosity, passion for innovation and creativity, and the ability to work independently. A capability to learn to study autonomoulsy and develop specialised skills required for this work is expected.
- Experience with modeling and simulation tools and basic knowledge in machine learning is a plus but not a requirement.
Starting date
By agreement
Contact
- The project will be supervised by Lena Buffoni (name.surname@liu.se)
- Secondary supervisor: Robert Hällqvist (name.surname@saabgroup.com)