Bergische Universität Wuppertal Fachbereich Mathematik und Naturwissenschaften Applied and Computational Mathematics (ACM)

Team Research Publications Teaching

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Strategic and Educational Aims

The MATHS-DISC consortium, consisting of five renowned universities from all over Europe, from Portugal to Ukraine, (Università di Verona, Bergische Universität Wuppertal, Igor Sikorsky Polytechnic Institute Kiev, Universidade de Lisboa and Université Grenoble Alpes) and the partner university NTNU Trondheim, collaborates with more than 20 partners from leading industry and research centers (e.g. Siemens, Intel, Bosch, Bayer, d-fine, uRoboptics, Vodafone Ukraine, IDOM, ENGYS, Otto Bock, DLR, Terranova, NeuronsLab, Computer Solutions SA, Royal IHC, ...) from different sectors and from all over Europe.

European industry must lead the digital and green transformation. By prioritizing worker well-being and harnessing new technologies, it can drive sustainable, human-centered growth. This aligns with the EU's focus on a people-centered economy, a green deal, and a digital Europe. Mathematics is fundamental to this transformation, providing a rigorous framework for understanding and solving complex problems. It's essential for AI development, material design, process optimization, and data analysis. As the world becomes increasingly data-driven, mathematics' importance will only grow.

Key areas where mathematics plays a crucial role:

• Artificial Intelligence (AI): Developing new models and algorithms for AI, such as neural networks, that can learn from data and make predictions. These models are essential for developing innovative products and services, and for optimizing manufacturing processes.
• Material Design: Designing new materials and products, such as self-healing materials and bio-inspired materials. These materials have the potential to revolutionize a wide range of industries, from construction to healthcare.
• Process Optimization: Optimizing manufacturing processes, such as scheduling, routing, and inventory control. These optimization techniques help to reduce costs, improve quality, and increase productivity.
• Data Analysis: Analyzing and interpreting data to make informed decisions in a data-driven world. Mathematics is used to identify trends, patterns, and data anomalies. This information can then be used to improve decision-making in various fields, such as marketing, finance, and healthcare.

A solid mathematical foundation is essential for any advanced economy. It correlates with competitiveness and higher living standards. In the era of computational science, big data, AI, statistics and business analytics, the societal importance of the mathematical sciences is set to increase. The EU's recent introduction of the Artificial Intelligence Act underscores the influential role of AI in economic and societal development. Improved algorithms, not just improved machines, will be crucial as computing advances. Mathematics is emerging as a key factor in improving the performance, reliability, and robustness of AI algorithms.

Mathematics is a critical tool for the challenges of Industry/Society 5.0. In the future, it will play an increasingly important role in developing innovative solutions for a more sustainable, prosperous, and equitable future.

European Network Team:

• Giandomenico Orlandi (Verona, Lead)
• Matthias Ehrhardt (Wuppertal, Co-Lead)
• Dan Tavrov (Kiev)
• Christophe Picard (Grenoble)
• Cláudia Nunes (IST Lisbon)


• Elena Celledoni (Trondheim, associated)

Here below some (incomplete) information:

MATHS DISC Programme

• fully integrated in the Partner Institutions
• delivers a multiple degree among the following ones:
  • MSc in Mathematics at UNIVR, study path MATHS-DISC;
  • MSc in Computer Simulation in Science at BUW;
  • MSc in Applied Mathematics at ISKPI, study path Data Science and Mathematical Modelling;
  • MSc in Mathematics at ULIS;
  • MSc in Mathematics and Applications at UGA, study path MSIAM - Industrial and Applied Mathematics.

• High profile training in mathematical,computational and data science/AI skills to handle complex problems for the new industrial, economical and societal era
• Integration of 3 key enabling technologies to minimise re-skilling along professional careers:
  • COMPUTING & SIMULATION
  • MODELLING & OPTIMIZATION
  • DATASCIENCE & AI
• Specialisation paths in 8 main domains central to digital & green transition:
  • Computational Intelligence & Complex Systems Optimization;
  • High Performance Computing;
  • Scientific Machine Learning;
  • Computational Finance & Circular Economy;
  • Energy Markets;
  • Agrifood, fisheries, environment;
  • Logistics & Transports;
  • Health and Biomedicine;
• internships / master thesis in R&D laboratories at industry and research partners;
• Research environment of excellence;
• wide network of industrial and academic partners (Europe/worldwide);

• exciting multicultural ambient, mobility, summer schools;
• student services and support - scholarships; care of students with special needs; promotion of equal gender opportunities

WHEN TO APPLY

• Main application phases: between January and February for students applying for EMJM scholarships, targeted regions scholarships, or Consortium funded scholarships.
• Second application phase: between May and June, for self-funded students

PREREQUISITES

• Students with first university degree (at least 180 ECTS credits in EU system/equivalent); at least 3 years of study at Bachelor of Science level in Mathematics, Applied Mathematics or related fields (Physics, Engineering, Computer Science, Economics, Statistics), with a strong mathematical background.
• Recommended maths prerequisites:
  • Basic knowledge of Calculus (18 ECTS),
  • Linear Algebra (6 ECTS),
  • Numerical Analysis (6 ECTS),
  • Programming skills (6 ECTS),
  • Statistics (6 ECTS).
• BSc degree must be obtained:
  • before 31 July for non-EU students
  • before 30 September for EU students

DOCUMENTS TO BE PROVIDED

• national ID/Passport;
• official academic transcript of records/degrees obtained at the time of the application (level 6 ISCED mandatory) with official certified English translations;
• CV in Europass format;
• motivation letter; and 2 letters of recommendation;
• choice of:
  • 3 mathematical background BSc courses for the selection interview;
  • type of Scholarship (EMJM, targeted region Scholarship, Consortium funded Scholarships, if available);
  • study plan (preferred Partner Institutions (PIs) for SEM1 - SEM2, preferred Specialisation Path for SEM3 - SEM4)
• proof of English Proficiency; If native language is not English → required to pass a recognised international English test (not older than 3 years at the time of the application):
  • TOEFL: CBT 220, ITP 550, IBT 80; Cambridge B2 First Test: 173 or higher; Cambridge C1 Advanced Test: 160 or higher;
  • IELTS: 6.5 or higher; TOEIC: 800.
  No other test is recognised. Applicants who carried out their studies in English (official confirmation letter from their university is needed) are eligible without providing such a test result.

Note: This is only a temporary website. In the future we will link to mathsdisc.eu.

Note2: The acronym MATHS-DISC symbolises a circular disc whose sectors stand for the various fields of applied mathematics: modelling, stochastics, numerical simulation and optimisation. In our EMJM programme, these traditional fields of mathematics are closely interlinked with current issues such as machine learning, digital twins and quantum computing, in line with the MSODE approach (Modelling, Simulation and Optimisation in Data-rich Environments). It is precisely this focus and the corresponding expertise of the MATHS-DISC consortium that makes this EMJM programme unique.