Data driven research is becoming increasingly important for many research activities at Chalmers. A large need also exists for research connected to energy transitions to meet climate targets. As new sources of data become available connected to energy and climate research there is potential for innovative research, but this does not come without related challenges. To extract valuable patterns from large data sets and handle the challenges, the Energy Area of Advance, CHAIR (Chalmers AI Research Centre), and ICT Area of Advance, issue this call to provide funding and expertise for research projects, together with the Data Science Research Engineers (DSRE) initiative funded by Chalmers e-Commons.
All projects have to include an emphasis on methods from data science and machine learning to use and extract patterns from data in the domains of energy and climate research. The funding applied for has to be used during an expected project duration of approximately 6 months, and 1-2 data science research engineers will provide support (outside the budget applied for) to implement and evaluate methods for data handling and analysis in the projects.
We welcome proposals in a relatively wide span: Ranging from the relevant and basic natural sciences, to the design, prototyping, and analysis of energy and climate-related technologies, on to energy and climate systems analysis. Examples related to energy technologies include electricity grids, process industries, energy end-use, energy conversion technologies, technology innovation systems, and energy in transport. One of the aims is to create new collaborations between the research areas Energy, Climate, and ICT, by supporting specific research projects in need of extracting patterns and using novel methods to analyse data.
- The data science research engineers will provide collaboration and support in new, or existing projects, by application of data science and AI methods to extract patterns out of one or a few specific data sources to answer the research questions at hand.
- The level of involvement of the data science research engineers should be not less than 30% of full time equivalent, and not larger than 50% full time equivalent during a period of 6 months.
- The projects should preferably start in August/September 2021. Exact date can be discussed.
- The budget applied for should not exceed 200 kSEK including indirect costs (OH). The budget can cover personnel costs, the purchase of equipment and data, or to cover time for researchers working on the related research project. The budget should not cover the involvement of the data science research engineers which is provided as part of the project.
- The proposal for the support and collaboration should have a connection to energy and/or climate research with clear potential and/or clear challenges to analyse the data. It is useful to highlight what data is already available, or what data collection from what data source (natural, technological, or social) that needs to be performed during the scope of the project.
The proposal form:
The application is supposed to be simple and straightforward without extensive overhead: It should be maximum 3 pages long (preferrably 1-2 pages to describe the background and the main research idea). Please use font 11pt Times–roman. A one-page CV of the main applicant and main project participants should be added. Maximum four such CVs can be added on.
The proposal should include:
a) Project title.
b) The main applicants: Name and e-mail and department.
c) The preferred starting date and ending date for the project.
d) A short overview of the project, with its research challenges and objectives and what novel possibilities you see in using data science or AI in your domain/research area.
e) A description of the type, size and availability of the data to be used in the projects including current availability and any restrictions in of use from intellectual property restrictions or so.
f) A concrete description of how you would start to work together with the data science research engineers to extract patterns from data.
g) The different types of expertise in the project (what type of expertise, and the expected involvement). Note: interaction with the DSRE team about this during writing of the proposal is recommended, see below.
h) The expected outcome (including dissemination/publication plan) and its potential for further research/activities.
i) The project overall time-line and budget (expenses on your side); in the budget, please clarify planned spending during 2021 and 2022 as the project is expected to run into 2022.
Submission deadline: June 6, 2021
Notification: June 2021
Expected project start: Aug/Sep 2021
- How innovative is the project in your research domain?
- How central is the use of data sources in the project?
- How high is the potential impact of the project for its research field?
- Cross-disciplinarity: Does the project mix ideas or researchers from more than one discipline?
- Are there methods from data science and machine learning to extract patterns from data?
The unit of data science research engineers is available to provide brief feedback about the proposals during the weeks leading up to the submission deadline, drawing on experience from previous projects
. This will ensure writing a proposal that clarifies available data and proposes relevant methods. They can be contacted through the mailing list email@example.com to seek feedback in the formulation of the proposal.
The application should be submitted as one PDF document to
The proposals will be evaluated by the AoA Energy management group and a selected group of senior researchers across different areas and departments at Chalmers, and will be decided by the directors of the AoA Energy management group, director of CHAIR, and the unit manager of the data science research engineers.