Field of Research & Scope

Despite remarkable advances in generative AI, building systems that are reliable and trustworthy in real-world deployments remains an open challenge. Current models frequently fail to respect hard constraints, lack grounding in verifiable knowledge, and produce opaque, unpredictable outcomes, limitations that are particularly problematic in safety-critical domains such as healthcare or industrial automation, and that undermine user trust in intelligent everyday environments. Neurosymbolic AI offers a path forward by integrating symbolic knowledge (e.g., logical rules and knowledge graphs) with subsymbolic approaches (e.g., neural networks), combining the flexibility of learning-based methods with the rigor and interpretability of symbolic reasoning.

The two PhD students will work collaboratively on related but independent research. The first will investigate how symbolic knowledge can be integrated into learning and inference (going beyond post-hoc constraints to actively shape how models reason and generalize) and will develop frameworks for selecting between symbolic, subsymbolic, and hybrid architectures, evaluated in real-world settings such as industrial automation and regulation-sensitive environments. The second PhD student will focus on the human side of trustworthy AI, designing neurosymbolic AI systems that interact with users in ways that are transparent, explainable, and privacy-respecting, addressing open challenges in multimodal perception, scalable reasoning, and personalization in smart environments.

Candidates with backgrounds in machine learning, symbolic AI, knowledge representation, human-computer interaction, or related areas are encouraged to apply.

We offer

• Collaborations: The INSYT lab enjoys close collaborations with leading research labs across Europe, as well as strong industry connections providing direct access to real-world issues and possible test environments. The lab also collaborates with researchers within IT:U and supports co-supervision with other IT:U founding professors.
• International and interdisciplinary network: Selected candidates will benefit from an active research network spanning academia and industry, with particular strength in Switzerland and Italy through collaborations with institutions such as the University of St. Gallen, University of Lausanne, Università della Svizzera Italiana, Empa, and University of Bologna.
• Professional and personal development: As founding members of a new lab, the two PhD students will have a unique opportunity to help shape its research agenda and culture. They will receive close, hands-on mentorship drawing on the PI's broad international experience across multiple research environments in industry and academia and will be strongly supported and encouraged to publish at top venues and produce high-impact research.

Responsibilities & Tasks

• Conduct research 
• Write and publish scientific papers
• Attend national and international conferences
• Collaborate with other research groups on an interdisciplinary basis
• Contribute to academic teaching (up to 2 weekly credit hours)
• Support the research group in preparing applications for third-party funding
• Comply with the institution’s academic standards and ethical guidelines

Skills & Qualifications needed

Required:

• A master's degree in computer science or a related field
•  Programming proficiency
• Background in machine learning and knowledge of symbolic AI
• Strong written and oral communication skills in English (CEFR C1)
• Ability to work independently and take initiative in a research setting
• Ability to collaborate in an interdisciplinary team
• Strong interest in human-centered AI

Desirable:

• Experience with knowledge representation and reasoning (e.g., knowledge graphs, ontologies, inference rules, RDF, OWL, SPARQL)
• Experience with multimodal data (e.g., text, vision, or sensor data)
• Interest in the societal and practical implications of AI deployment in real-world environments

What you can expect

• Innovative and stimulating working conditions in an interdisciplinary, international research environment.
• Office kitchen with complimentary basic supplies.
• Austrian “KlimaTicket OÖ” (unlimited travel on all public transportation within Upper Austria).
• We offer a gross salary in line with the FWF of EUR 2.832,10 on a 30h basis. 
• Optional supplementary contracts (teaching or research) to an extent of up to 10 hours may be discussed during the hiring process.

Program Structure

IT:U offers a 4-year, structured PhD program.
 
In the first year, emphasis is placed on focused group work, research lab modules, and Project Integrated Courses (PICS). The first year concludes with a PhD Proposal Presentation. Over the next three years, students will develop and write their PhD theses. This is accompanied by interdisciplinary research seminars and work as a project assistant. The PhD program concludes after the 4th year with the submission and defense of the PhD thesis. 
 
Click here to view the curriculum. 

How to apply

Please fill in the online application form and upload your files at: https://apply.it-u.at/

• Curriculum Vitae
• Bachelor’s and master’s diploma (or equivalent)
• Bachelor’s and master’s transcript of records
• Motivational letter (2 pages max, include your research interest and mention any research experience you might have had)
• Up to 3 contacts of professors/collaborators for recommendations

We look forward to receiving your online application.

The positions will remain open until filled. Candidates are encouraged to apply early, as review of applications will begin on a rolling basis. The call will close on 30.04.2026.