Humboldt University of Berlin is inviting applications for a W3-S Professorship in Explainable Artificial Intelligence, jointly appointed with the Fraunhofer Institute for Digital Media Technology (Heinrich-Hertz-Institute, HHI). This role merges academic excellence with applied research, developing AI systems whose decisions remain clear, traceable, and trustworthy to human users. It bridges foundational theory with industry-driven innovation, advancing transparency in AI across diverse fields.
Humboldt University’s W3-S Professorship in Explainable AI offers a prestigious joint appointment with Fraunhofer-HHI, focusing on cutting-edge research in transparent AI systems. It combines world-class resources and collaboration opportunities, ideal for scholars eager to connect advanced algorithm development with practical, real-world deployment.
Position and Institutional Partners
The selected candidate will hold a W3-S full professorship within the Faculty of Mathematics and Natural Sciences at Humboldt University. The joint appointment with Fraunhofer HHI creates an integrated research environment where university-level scholarship meets the practical challenges of AI deployment in signal processing and digital media.
Academic and Industry Synergy
This appointment offers a dual platform:
- Academic track – leading research projects, supervising doctoral candidates, and shaping teaching programmes.
- Applied track – leveraging Fraunhofer HHI’s infrastructure for prototypes, funding access, and industry collaboration.
Together, they enable the development of AI
Research Focus
Core Area: Explainable Artificial Intelligence (XAI)
The professorship focuses on methods and models that are high-performing yet fully interpretable. Key goals include:
- Model transparency – enabling stakeholders to understand AI outputs.
- Trustworthiness – ensuring AI systems can be confidently applied in sensitive domains.
- Auditability – aligning processes with regulatory and ethical standards.
Interdisciplinary Integration
Work will span multiple fields:
- Signal processing expertise from HHI, especially in audio and media AI.
- Advanced machine learning, including deep neural networks and probabilistic approaches.
- Human-computer interaction (HCI) to design explanations that align with user understanding.
- Ethics and law to evaluate societal and regulatory implications.
The aim is to form a research hub producing high-impact publications, trained experts, and competitive interdisciplinary grant proposals.
Eligibility and Academic Profile
Required Qualifications
Applicants should bring:
- A strong publication track record in AI interpretability and transparency.
- Proven success in securing research grants, especially for cross-disciplinary projects.
- A teaching portfolio demonstrating theability to engage advanced undergraduate and doctoral students.
While no strict requirements on years of experience are stated, competitive applicants often hold senior academic posts or equivalent research leadership positions.
Desirable Expertise
- Significant work in designing and assessing explainable AI systems.
- Experience with industry collaboration, ideally in media or signal processing.
- A strategic vision for curriculum innovation, introducing modules on explainability, fairness, and AI ethics.
Application Process
Required Documentation
Applicants should prepare:
- Cover letter explaining alignment with the role.
- Comprehensive CV listing publications, projects, and leadership roles.
- Research statement outlining prior work and future XAI agenda.
- Teaching philosophy with course proposals and supervision approach.
- References from established academics.
Submission and Timeline
Candidates should check the official position notice for submission methods, format, and data protection details. Typical stages include:
- Application review.
- Seminar or sample lecture for shortlisted applicants.
- Panel interview with Humboldt University and HHI representatives.
- Final selection and formal appointment.
Application deadlines are usually set 2–3 months after announcement
Why This Role Stands Out
Leadership in a Growing Field: Explainable AI is central to the next phase of AI adoption. This professorship offers the platform to influence international standards and practices while shaping future generations of AI practitioners.
World-Class Resources: Humboldt University’s academic strength, combined with Fraunhofer HHI’s applied research capacity, provides unmatched access to infrastructure, industry networks, and innovation funding.
Berlin Advantage: Based in Berlin, one of Europe’s most vibrant research cities, the role connects you with a rich ecosystem of universities, institutes, startups, and cultural resources.
Preparing a Strong Application
Showcase Interdisciplinary Impact: Highlight past work that merges AI interpretability with HCI, ethics, or media processing — such as explainable speech recognition or multimedia analysis tools.
Emphasise Teaching Innovation: Propose course structures that address both the technical and ethical dimensions of AI, preparing graduates to navigate the future AI landscape responsibly.
Demonstrate Research Leadership: Include evidence of managing research teams, leading large-scale projects, and attracting competitive funding — especially with industry-academia partnerships.
Summary
The W3-S Professorship in Explainable Artificial Intelligence at Humboldt University, in partnership with Fraunhofer HHI, is an exceptional opportunity for scholars ready to lead in one of AI’s most crucial areas. Combining academic freedom with strong applied research backing, it offers the tools, networks, and visibility
Feature Summary
Feature | Details |
Position | W3-S Professorship in Explainable Artificial Intelligence |
Host Institution | Humboldt University of Berlin – Faculty of Mathematics & Natural Sciences |
Partner Institution | Fraunhofer Institute for Digital Media Technology (HHI) |
Focus Area | Research, teaching, and development of interpretable AI systems |
Eligibility | Experienced AI scholars with interdisciplinary expertise |
Application | Letter, CV, research & teaching statements, references |
Location | Berlin, Germany |
Benefits | Leadership role, cross-sector collaboration, global research visibility |
Timeline | Application window open; includes seminar and interview stages |
Official Page |
Frequently Asked Questions (FAQs)
It is a senior academic position focusing on transparent, interpretable AI systems, jointly appointed with Fraunhofer HHI in Berlin.
Experienced AI researchers with strong publication records, proven teaching skills, and expertise in explainability, transparency, and interdisciplinary collaboration can apply.
The role covers explainable AI, machine learning, human-computer interaction, ethics in AI, and applied projects in signal and media processing.
The appointment is shared, enabling access to Fraunhofer HHI’s applied research projects, industry partnerships, and advanced technical infrastructure.
The professor will teach AI-related courses, mentor doctoral candidates, and develop interdisciplinary curricula in explainable and ethical AI.
Highlight interdisciplinary research, industry collaborations, teaching innovation, and evidence of securing competitive grants in AI or related fields.
It is based at Humboldt University’s Faculty of Mathematics and Natural Sciences in Berlin, Germany, with joint work at Fraunhofer HHI.
It includes application review, seminar presentation, faculty and partner interviews, and final appointment confirmation.
Explainable AI ensures transparency, trust, and accountability, making AI decisions understandable for users, regulators, and stakeholders.
It offers leadership in a growing field, access to Berlin’s research networks, and resources from both Humboldt University and Fraunhofer HHI.
