Wallenberg AI, Autonomous Systems and Software Program is Sweden’s largest individual research program and provides a platform for academic research and education, fostering interaction with Sweden’s leading companies. The program addresses research in artificial intelligence, autonomous systems, and software as enabling technologies for developing systems acting in collaboration with humans, adapting to their environment through sensors, information, and knowledge, and forming intelligent systems of systems. WASP strengthens, expands, and renews the national competence through new strategic recruitments, a challenging research program, a national graduate school, and collaboration with industry. WASP aims at increasing the gender balance and building a culture based on inclusion and diversity. The program is conducted in close cooperation between leading Swedish universities to promote the competence of Sweden as a nation within the area of AI, autonomous systems and software.

Wallenberg Initiative Materials for Sustainability (WISE, https://wise-materials.org) is the largest-ever investment in materials science in Sweden and encompasses major efforts at Sweden’s leading universities over the course of (at least) 10 years. The aim is to create the conditions for a sustainable society by researching the next generation of ecofriendly materials and manufacturing processes. This will also facilitate better technology for energy systems of the future, and to combat climate change, pollution, and toxic emissions. Specifically, efforts will be devoted to identify new or significantly improve materials, which provide a distinct advantage in physical, chemical, biological, or functional performance when compared to existing materials and technologies. This relates to materials that demand fewer resources, are less environmentally hazardous, and enable sound and efficient recycling processes. WISE will also explore materials that, when used in energy technology, generate less negative climate impact under operation, while offering high performance and efficiency when in action at large scales.

Aim and scope

The aim of the call is to initiate the collaboration between WASP and WISE in the areas of AI, autonomous systems and software and material science for sustainability. The projects should be conducted during 2024.

The project should be based on a joint research plan, including one Principal Investigator (PI) at WASP and one PI at WISE. The PIs eligible to apply, one from WASP and one from WISE, are defined under “Who can apply”.

Who can apply?

A project is jointly applied for by one PI that is eligible to apply for WASP projects and one PI that is eligible to apply for WISE projects. A PI can be involved in only one application.

The WASP PI should be affiliated with one of the WASP partner universities Chalmers University of Technology, Linköping University, Lund University, KTH Royal Institute of Technology, Umeå University or with one of the Affiliated Groups of Excellence at Örebro University, Uppsala University or Luleå University of Technology.

The WISE PI should be affiliated with one of the six partner universities, Chalmers, KTH, Linköping University, Uppsala University, Stockholm University, and Lund University, or with Luleå University of Technology, or with one of the affiliated groups of excellence at Karlstad University, Umeå University, and Örebro University.

The call aims to achieve a gender balanced outcome as a whole, and possibly in every project.

Budget

This is the first call for collaboration projects between WASP and WISE.

The maximum budget for one project is 1 MSEK. 30 projects are expected to be funded within the total budget for the call.

Use of Funding

The intention is that the funding should be used for:

  • Use of funding is flexible but should be motivated and specified. It can for instance be salary, travel, and consumables.
  • Indirect costs are covered according to the following:
    WASP – The costs include a maximum compensation of 5% surcharge for premises and a maximum of 18.4% surcharge for Indirect Costs.
    WISE – The costs include a maximum compensation of 3.5% surcharge for premises and a maximum of 18.45% surcharge for Indirect Costs.

Proposal Structure/Format

  1. Name of the project
  2. Names and affiliations of the two PIs
  3. Project plan (max 2 pages) with clearly specified subject area and focus including:
    1. challenges
    2. work plan including forms of collaborations
    3. expected results
  4. Explanation of the collaborative benefits and the role of each of the PIs and parties (max 1 page)
  5. Short CV and top publications for the two PIs (max 2 pages each)
    1. scientific merits
    2. international research experience
    3. pedagogical skills and merits
    4. experience to collaborate with academia and industry
  6. Commitment letter from hosting university, should be signed by the Head of the Department.
  7. Short description of the use of funding

Evaluation Criteria

Projects will be evaluated considering scientific excellence and impact from a materials science for sustainability perspective as well as from an AI, Autonomous Systems and Software perspective, alike. Specifically the following criteria will be used:

  • Scientific quality
  • Novelty and Originality
  • Synergies in the planned collaboration
  • Feasibility
  • Industrial and societal relevance
  • Merits of the applicants
  • Diversity of gender of the applicants

We will also consider:

  • Open science and data sharing aspects
  • Impact on WASP-WISE community

Submission

The proposal should be submitted as a single PDF file to the application portal no later than 2023-09-30.

Timeline

2023-06-20   Call opens

2023-09-30   Application deadline

2023-12-08   Decision communicated

Match making

To find potential collaborators, common topics, exchange ideas and opportunities, and raise awareness of competencies on each side, we invite you to submit an abstract. An online report of the abstracts will be available in an abstract collection until the call closes.

Submit an abstract

Abstract collection

View all calls
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