Research Associate Digital Energy Systems (80-100%)

The Lucerne School of Engineering and Architecture is the leading educational and research institution in its field in Central Switzerland. The School offers practical bachelor’s and master’s degree programs and a variety of continuing and executive education programs, and also carries out applied research and development. It is one of six Schools making up the Lucerne University of Applied Sciences and Arts with its 1,800-plus staff and around 11,500 degree and continuing education students.

For our research and teaching activities in the field of digital energy and electric power, we are looking for a competent personality as

Research Associate Digital Energy Systems (80-100%)

As a Research Associate Digital Energy Systems you will contribute to the decarbonisation of our power system through the application of advanced data techniques, algorithms and concepts in electrical power systems, grid modelling, and control. This will include:

• Developing approaches and techniques for solving grid challenges associated with renewable energy integration, managing battery systems or managing distributed energy resources
• Designing, implementing and testing models
• Deploying and testing these techniques in real-world settings and within the laboratory
• Interacting and collaborating with diverse industrial and research partners, including network service providers, energy market operators, start-up companies, large industrial companies, and other researchers at HSLU and across Switzerland
• Contributing to research proposals and carrying out research investigations, requiring originality, creativity and innovation
• Communicating research results to a range of audiences, including industrial partners and the scientific community

• PhD in power systems or a related field. Master’s degree in a relevant engineering field will be considered.
• The ideal candidate should have a solid background in machine learning, deep learning and data analysis
• Experienced in power systems modelling, optimization and analysis
• The ideal candidate should have experience with machine learning toolboxes and frameworks in particular with the application of data-driven techniques to power system problems. Strong programming skills in Python, R or Matlab is desirable
• Demonstrated ability to work effectively in a collaborative and multi-disciplinary scientific or commercial environment
• Demonstrated success in expressing ideas clearly through oral and written skills in German and English language