Part-time lecturer for Data Science and Practical AI Projects (m/f/d)
About IMC Krems
Our university offers students, lecturers and employees the perfect environment for their personal development. We take responsibility for the best education and thus create important values for the future of our society. IMC Krems is committed to promoting equal opportunities and diversity. This means that we particularly welcome applications from women, people from international backgrounds and people with disabilities or chronic conditions.

international
meaningful
curious
IMC. It´s all in me.
Your tasks
You are a leader
You will teach in your specialist subject area on the Bachelor’s degree programme in Informatics, amounting to 6 SWS.
The course is advertised for the summer term 2027.
Your profile
You have a distinctly international outlook
- A completed technical or educational university degree (PhD)
- University teaching experience
- Data science ecosystem: Proficiency in libraries such as Pandas, NumPy and Scikit-Learn, as well as visualisation tools (Matplotlib, Seaborn, Plotly).
- Practical AI / Machine Learning: A fundamental understanding of classical machine learning methods, as well as practical experience with modern AI technologies.
- Supervision of practical AI projects: Coaching student teams through the entire AI lifecycle (problem definition, exploratory data analysis, modelling, validation, presentation).
- Active member of the scientific community (as reflected in memberships, conference attendance and peer review work)
You are highly committed and willing to learn and have excellent organisational skills. A professional demeanour, respect for colleagues and leadership abilities are very important to us. We expect our people to work efficiently with an emphasis on achieving targets, and to adopt an entrepreneurial, strategic approach.
Your benefits
We offer you appreciative services
We offer you appreciative services
Flexible working models
State-of-the-art technology
International environment
Payment is made on a fee basis.
