The Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) is planning to publish – later this year – a call for proposals jointly with the National Natural Science Foundation of China (NSFC) in mathematics.

In order to facilitate the creation of scientific contacts between researchers from China and Germany who may wish to submit Sino-German project proposals in the framework of the upcoming call, the Sino-German Center in Beijing will host a “Matchmaking Workshop”. This workshop will take place from 15 to 17 September 2025. The topic of the workshop and the subsequent call is “Intelligent Numerical Mathematics”.

In recent years, the combination of numerical methods and learning-based approaches has gained an ever-increasing interest as a research field within Numerical Mathematics and Scientific Computing. The suggested topic “Intelligent Numerical Mathematics” (iNum) will foster the development of the two emerging fields of learning-based numerics and numerically efficient learning methods. Here, both fields are viewed as research topics within Numerical Mathematics and Scientific Computing. This viewpoint is supported by a fast-growing number of publications and presentations at conferences across Applied Mathematics and Computational Science and Engineering (CSE).

By using learning-based numerics, the range of tractable problems as well as the efficiency and robustness of numerical methods can be tremendously enhanced, for example by 

• learning of numerical parameters such as relaxation parameters, adaptivity criteria or regularisation weights,
• learned components in model reduction or multi-scale methods,
• generation of good initial guesses or preconditioners for iterative solvers,
• decisions between different options such as parallelisation strategies or different types of solvers for (non-)linear systems of equations,
• load balancing based on learned performance models. 

Here, challenges are expected in terms of stability requirements, convergence or, more general, quality guarantees. In the field of numerically efficient learning methods, new or improved numerical algorithms are used to tune state-of-the-art learning methods. Increased computational efficiency and parallel scalability as well as numerical robustness of modern learning algorithms can be expected as scientific output. For example, improvements in the training phase are expected by 

• enhanced optimisation methods,
• sparsification, regularisation and error control,
• parallel numerical methods with improved scalability and reduced communication. 

Learning methods challenge the traditional numerical approaches in many of the aforementioned aspects and pose new questions for research in Numerical Mathematics and Scientific Computing. 

There are strong research groups in both China and Germany for the two research fields of learning-based numerics and numerically efficient learning methods. For this reason, the DFG and the NSFC aim to enable the respective scientific communities to join forces and to take this topic to a new scientific level.

The aim of the workshop is to bring together researchers from China and Germany in order to present their current research and to exchange research ideas for possible joint research work with relevance for the planned call. Researchers who meet the eligibility requirements for proposals within the DFG’s individual grants programme are invited to submit an abstract for a possible 30-minute talk together with their academic CV.

In order to participate in this workshop (as a scientist from Germany), you need to apply by 1 July 2025 at the latest. Applications (as PDF files) need to be submitted via the DFG’s elan portal(externer Link). After logging in, please use the online form for “Letter of Intent / Declaration of Interest” (Proposal Submission > New Project > Letter of Intent / Declaration of Interest). There is no template for the abstract; however, for the CV, please refer to the respective template (DFG form 53.200(interner Link)).

The abstract should contain a title and a scientific summary (half a page) of the intended talk, also referring to the content of the workshop as described above. Additionally, possible previous or ongoing collaborations with scientists in China can be mentioned.

Decisions will be communicated by mid-July.

The Sino-German Center will cover travel and accommodation.

Please note that participation in this workshop is not a pre-requisite for the submission of a project proposal in the planned call.

If this is the first time you are submitting a proposal to the DFG, please note that you must register in the elan portal before you can submit your proposal. You must do so by 26 June 2025. You will normally receive confirmation of your registration by the next working day.

Equity and Diversity

The DFG strongly welcomes proposals from researchers of all genders and sexual identities, from different ethnic, cultural, religious, ideological or social backgrounds, from different career stages, types of universities and research institutions, and with disabilities or chronic illness. With regard to the subject-specific focus of this call, the DFG encourages female researchers in particular to submit proposals.

Good Research Practice

According to a resolution of the DFG General Assembly, DFG funding may only be awarded to research institutions that have implemented the guidelines laid down in the Code of Conduct for Safeguarding Good Research Practice(externer Link) in their own regulations. The management of your institution is responsible for implementing the guidelines in a legally binding manner. In order to avoid delays in the disbursement of funding, please verify implementation within your institution in good time. For information regarding the implementation, please refer to the Research Integrity Portal(externer Link). If you have any questions on this subject, please contact the Research Integrity team(externer Link) at the DFG Head Office.

Further Information 

Please find more information concerning the Sino-German Center for Research Promotion in Beijing here(externer Link).

Contact Persons at the DFG Head Office

Programme contact

Dr. Carsten Balleier, Mathematics and Engineering Sciences 2, phone +49 228 885-2063, carsten.balleier@dfg.de(externer Link)

Dr. Frank Kiefer, Mathematics and Engineering Sciences 2, phone +49 228 885-2567, frank.kiefer@dfg.de(externer Link) 

Administrative contact

Silke Seiler, Mathematics and Engineering Sciences 2, phone +49 228 885-2751, silke.seiler@dfg.de(externer Link)

Privacy Policy

We, the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), take the protection of your personal data and its confidential treatment extremely seriously. Therefore, please refer to the DFG’s Privacy Policy(interner Link). If you intend to transmit personal data of third parties, please make sure to do so only if the necessary legitimation under data protection law exist. Before transmitting data of third parties to the DFG, please forward the DFG’s Data Protection Notice to the individuals affected (data subjects). If there is a legitimate interest not to inform individuals beforehand (e.g. for reasons of secrecy or in case of a nomination or candidate proposal), these individuals should be informed no later than at the time of publication.