Professorship (W2) in Artificial Intelligence and Intelligent Systems (100%) (m/f/d)

Fixed-term employment contract (initially for two years) Full-time Hannover, Munich, Leipzig, Remote Published on Application deadline: Earliest start date:

Teaching load of 18 SWS velpTEC is an education institute focused on innovative technologies, combining experience from business, future studies, and new educational approaches. Through our educational offerings, we support people in strengthening their skills for the future in a practice-oriented way, helping them actively shape their own paths in life - and from 2027 onward, also in higher education.

VTH - University of Applied Sciences in foundation (in Gründung) is a private university of applied sciences currently undergoing the process of state recognition through the Lower Saxony Ministry of Science and Culture. Our degree programs are launching in the fields of digital technologies, engineering, and innovation-driven management - with a clear commitment to continuously expanding our portfolio and responding to new developments.

We understand teaching as a space for shaping solutions for tomorrow. Our approach is project-based, competency-oriented, and closely interlinked with practice.

We are looking for individuals who are eager to break new ground in higher education and want to actively help shape our innovative learning environment.

We are filling a W2-Professorship in Artificial Intelligence and Intelligent Systems (100%).

Program development

• Contributing to the development of the Master's program in Neurorobotics, and assisting in recruiting students

Masterclasses and expert seminars

• Conducting live sessions on machine learning, decision-making models, adaptive systems, and AI-supported quality assurance in English

Student supervision and examination formats

• Providing academic guidance, mentoring, and support for project and research work; designing and evaluating portfolio assessments, exams, and master's theses

Applied research

• Conducting practice-oriented research and transfer projects in the areas of AI, robotics, and autonomous systems - in cooperation with industry, healthcare, mobility, international partners, and research institutions

Funding and cooperation

• Initiating research collaborations and acquiring third-party funding to strengthen applied research at our university

Publications and presentations

• Publishing research findings in academic journals and at relevant conferences, as well as representing the university at specialist presentations and industry events

Transfer

• Willingness to participate in research-related product developments, founding/start-up ventures, and patent applications

University development

• Contributing to the university's academic self-governance, helping to further develop the range of study programs, and participating in international collaboration

Recruitment requirements

• A completed university degree
• Pedagogical-didactic aptitude confirmed through practical experience
• Special aptitude for in-depth independent scholarly work, generally evidenced by an above-average doctorate in the fields of Computer Science, Mathematics, Physics, Engineering, or related fields
• Special achievements in the application or development of scientific findings and methods over at least five years of professional practice, of which at least three years must have been carried out outside the higher education sector - preferably in artificial intelligence, machine learning, robotics, or data science
• The ability and willingness to conduct teaching, research, and transfer activities in English.
• Willingness to develop and further build higher education teaching competencies - particularly in (generative) AI-supported teaching.
• Innovative spirit in teaching: Motivation to develop and apply new didactic formats in AI and intelligent system education.
• Interdisciplinary openness: Readiness to collaborate with colleagues in robotics, neuroscience, additive manufacturing, and digital business.
• Practice and transfer orientation: Proven experience in applying AI technologies in real-world contexts such as industry, healthcare, or mobility.
• International perspective: Experience in international contexts or motivation to integrate global developments in AI and intelligent systems into teaching and research.
• Commitment to institutional development: Willingness to actively shape the foundation and growth of a new university.
• Research profile: A visible research focus in deep learning, reinforcement learning, intelligent control systems, or AI-driven sensor technologies.
• Knowledge and technology transfer: Understanding research as a bridge between science, industry, and society.
• The opportunity to shape the development of a new university and its programmes right from its foundation.
• A professorship with a clear focus on teaching, quality assurance, and applied research.
• Interdisciplinary collaboration with colleagues in r