Graduates will be able to design and implement state-of-the-art HPC, QC and CFD methods and algorithms to innovatively solve complex problems in areas such as scientific research, weather forecasting, geophysical flows and drug discovery

AT BUW

• Transregional research network “Hadron Physics from Lattice QCD” (2008–2020), funded projects EU MSC ITN HPC-LEAP “High Performance Computing in Life Sciences
• Engineering and Physics” (2015–2018), EU MSC ITN STIMULATE “SimulaTIon in MUltiscaLe physicAl and biological sysTEms” (2018–2021) and EU Doctoral Network AQTIVATE “Advanced computing
• QuanTum algorIthms and data-driVen Approaches for science, Technology and Engineering” (2023-2027)
• Coordination of the Doctoral Network “ModConFlex - Modelling and control of flexible structures interacting with fluids” (2023-2027)
• EU FET Flagship Project “Human Brain Project” (2012–2022)
• Cooperation with the Jülich Supercomputing Centre and the Institute of Neuroscience and Medicine at the Jülich Research Centre.
• In 2019, BUW was awarded a major 2.4M Euro grant for the enhancement of its computational infrastructure (DFG major instrumentation initiative).
• Partnership with Intel.

Graduates will be able to apply machine learning and soft computing techniques to solve problems in a variety of domains involving data analysis, pattern recognition, and optimisation. They will also be able to develop innovative human-centred AI systems that are safe, reliable, and easy to use

AT BUW

Many specialisation courses related to Machine Learning and AI methods, in particular hybrid methods.. Several internships/MT opportunities at the Interdisciplinary Center for Machine Learning and Data Analytics and at partner companies Bayer, Computer Solutions

Graduates will be able to use MSODE methods to develop financial models, manage risk and optimise investment strategies. They will also be able to apply their skills to the circular economy, developing sustainable and efficient production and consumption systems

AT BUW

• Many specialisation courses on computational finance.
• Organisation of the series of ICCF – International Conference on Computational Finance with a special focus on “green finance”.
• Many internship/MT and development opportunities within EU funded projects on computational finance, circular economy and environmental modelling, CO2 emission rights trading, optimal CO2 taxation at partner company d-fine.
• Opportunities also at associated university NTNU, whose Strategic Research Area “NTNU Sustainability” offers internships/MT on the transition to a circular economy and sustainable production and consumption systems.

Graduates will be able to use MSODE methods to analyse energy markets, simulate energy systems, and forecast energy prices. They will also be able to develop strategies to optimise energy production, distribution, and consumption

AT BUW

• Leader of the Special Interest Groups – ECMI on computational finance and energy markets.
• Internships/MT opportunities at the (Wuppertal Institute for Climate, Environment and Energy ).
• Joint supervision of a number of MT with UNIVR on modelling price of electricity markets, including the use of AI and machine learning techniques.
• Partnership with Intel