As one of the largest private universities in Germany, SRH University is the innovative companion for students from over 140 nations. We are part of the leading education and healthcare provider SRH, which has been helping people to lead a self-determined life for over 50 years. We teach with passion and competence and focus on the professional and personal development of our students. At our forward-looking campuses, we offer a wide variety of study programs and models, hand in hand with business and practice. With our innovative and award-winning CORE didactics, we accompany our students individually on their path. They learn hands-on in small groups and interactive, project-based units. We see ourselves as an international, diverse and interdisciplinary community.

We are part of SRH – a leading provider of edu­cation and healthcare services with 17,000 employees. The SRH operates private colleges, education centers, schools and hospitals.

To strengthen our School of Arts, Information & Media, we are looking for a Professor of Applied Data Science at the Munich campus f/m/d in full-time starting from October 1, 2025. The position is unlimited.

Your responsibilities:

• Competence-oriented teaching at the Master's level in English, in the particular field of handling large amounts of data and machine learning, natural language processing and deep learning
• Supervision of case studies, internships and master thesis projects
• Research and publications in the field of Data Science
• Acquisition and implementation of – preferably interdisciplinary – research projects and projects with partners in professional practice
• Participation in the further development of the study program and in academic self-administration
• Participation in the university's international activities, in particular in the expansion and intensification of our network
• Willingness to travel to or work at other locations is an advantage

Your profile:

• Fulfillment of the employment requirements for professors according to § 47 LHG BW
• Special aptitude for scientific work is usually demonstrated by a qualified doctorate or excellent subject-related practice achievements
• Knowledge of Designing and Implementing Statistical Models, Statistical Data Analysis and Machine Learning
• Processing and analysis of complex and large datasets
• Practical knowledge with teaching experience with programming languages such as Python, R
• Experience with tools such as Tableau, Open Refine, Trifacta
• Relevant Publications in the domain of Applied Machine Learning, and Data Engineering
• Experience with handling and maintaining data infrastructure
• Independent and responsible way of working
• Substantial teaching experience in university is recommended
• Excellent written and spoken English knowledge
• Willingness to actively develop accompany learning processes according to the CORE Principle
• Willingness to use innovative teaching concepts and their further development using digital media and technologies as well as enjoyment of educating our students
• Network of contacts in the data science industry is advantageous

We offer:

• Work-life balance | Balanced work-life balance through mobile working and generous and flexible working hours
• Mobility | Business bike, subsidy for Germany ticket
• Further development | coaching pool, parenting compass, study discount at the Mobile University and employee appraisals
• Savings offer | Corporate benefits: discount store for employees only
• Equipment | Modern office and seminar equipment
• Security | Company pension scheme and value account
• Volunteering | #TeilDeinGlück and receive additional paid time off

We are looking for the best. In this, we pay special attention to personality, talent, willingness to achieve and character.

We emphasize expressly that all people - regardless of gender, nationality, ethnic and social origin, religion/ideology, disability, age and sexual identity - are all equally welcome here. Applicants with disabilities who have equal professional and personal aptitude will be given priority and/or training.

Kontakt

For further information please feel free to contact:

Prof. Dr. Jutta Milde, Phone +49 (0) 6221 6799-221

We look forward to receiving your appli­cation online via our career portal stating your earliest possible starting date and the reference number 14607.

We would like to point out that the application documents will be made accessible to the appointment committee and thus also to external third parties who are not part of the university. Depending on the federal state, these are experts from practice or other universities or student representatives who are members of the appointment committee in accordance with the appointment regulations in application of the respective state university laws.