Call for Collaboration in Innovative Technologies 2022

Pioneering applied technologies

This call for proposals seeks to transform highly innovative, fundamental knowledge obtained from advanced technological research into applied software technologies designed to have a substantial impact on research across all disciplines.

This call for proposals is intended for researchers from:

  • a domain-oriented research discipline with a focus on technology development, or
  • a technology-oriented research discipline (e.g. data science, computer science, AI),

who have a pronounced interest in making their research results applicable to other disciplines.

This call is open for proposals in the following two technology areas:

1. Digital Twins: Virtual Representations of the Real World

Digital twins are virtual representations of real-world objects or systems. Typically, digital twins are based on a combination of several models, sometimes supported by machine learning, and refined with real-time data. Coupled with interactive analysis and visualization, this technology opens up innovative avenues of research, allowing for real-world modelling at an unprecedented scale and extreme levels of detail. Moreover, it allows researchers and policy makers to run what-if scenarios, supporting decision making.

Possible research topics include, but are not limited to:

  • Model coupling and integration;
  • Uncertainty quantification;
  • Enhancing modelling and simulation capabilities with machine learning and surrogate models;
  • Data assimilation;
  • Interactive analytics.

2. SciML: Combining Machine Learning with Scientific Domain Knowledge

Combining machine learning with domain knowledge can yield models that work with less data, are more efficient in terms of computational processes and energy requirements, while they are also more accurate and more trustworthy. Moreover, an approach focused on capitalizing on domain knowledge can help avoid a well-known limitation of traditional machine learning methods: learning only from what they see. Combining machine learning with domain knowledge will make AI more widely applicable and attractive to domain researchers.

Scientific ML (SciML) seeks to address domain-specific data challenges and extract new insights from research data through innovative methodological solutions. SciML is explicitly not limited to the exact sciences only; it is applicable to all areas of research. SciML uses tools from both machine learning and scientific computing to develop new methods for learning and data analysis that are scalable, domain-aware and interpretable.

Possible research topics include, but are not limited to:

  • Non-traditional/low-cost data sources, data fusion. Extracting Insights from multiple sensors and sources;
  • Robust and reliable learning. Uncertainty quantification, stability, validation, performance metrics, and reproducibility;
  • Domain-aware and physics-informed learning. Hybrid models that include both data-driven and domain-aware components;
  • Interpretable/explainable machine learning.

Information Event

Does this call for proposals interest you? Find out more about the specific aims of the call for, as well as the role and expertise of the eScience Center in our video recording from our online information event on 5 April 2022 or download the presentation slides.

In-kind support from Research Software Engineers

Projects receive in-kind support. This means that a team of research software engineers (RSEs) from the eScience Center will work together with the applicants to develop the applicant’s (ongoing) technological advancements into a reusable, sustainable and fully engineered product, provide documentation, set up training events and help identify and connect to stakeholders.

A project may be requested for an in-kind budget of 3.0 PYR. The project duration should be between 24 and 36 months.

The organisation of at least two substantial workshops is mandatory. The main goals of these workshops should include technology development and user community engagement. The format and costs of the workshops should be negotiated with the eScience Center. Expenses of up to 30K EUR will be covered.

In addition to their specific focus on the development of advanced research software, RSEs at the eScience Center will help applicants interpret the results of their research and help make the tools and methods that emerge from the project (re-) useable for the wider research community. They will co-author research and methodological publications together with members of the research team.

Procedure and deadline

Project Proposition

  • Applicants are required to submit a Project Proposition before they can submit a Full Proposal.
  • As part of the proposition, a Letter of Commitment must be submitted, signed by the dean or director of the institution at which the LA is employed, detailing the LA’s minimal investment in the project in FTE per year.
  • The closing date for the submission of Project Propositions is Thursday 12 May 2022, 14:00:00 CET.
  • Selection of proposals to proceed to the next round, and notification of applicants will happen in June 2022.

Full Proposal

  • As part of the full proposal, a Software Management Plan must be submitted, signed on behalf of an institute or other formal entity.
  • The closing date for the submission of Full Proposals is Thursday 1 September 2022, 14:00:00 CET.
  • Applicants will be informed of the final decision in December 2022.

Contact details

Programme Management Netherlands eScience Center
Tel.: +31 (0)20 460 4770

Other call opportunities

We are always open for opportunities to collaborate with our colleagues! Be sure to check out our other calls for proposals.