Project Staff Member (PhD position)

  • Vienna University of Economics and Business
  • Research, development, teaching
  • Part time
  • published till: 11.12.2024
You want to understand how things are connected and make a fundamental impact? We offer an environment where you can realize your full potential. At one of Europe’s largest and most modern business and economics universities. On a campus where quality of work is also quality of life. We are looking for support at the

Institute for Data, Process and Knowledge Management
Part-time, 30 hours/week
Starting January 01, 2025, and ending after 4 years
 
We are seeking highly motivated and talented individuals to join our dynamic research team for combining symbolic and sub-symbolic AI. The successful candidates will conduct research at WU in collaboration with our partner institutes Johannes Kepler University Linz, AAU Klagenfurt, ISTA, TU Graz, and TU Vienna.
 
The vision of Bilateral AI is to educate a new generation of top-quality AI scientists with a holistic view on symbolic and sub-symbolic AI methods. Training and mentoring of young researchers is a central activity, which combines groundbreaking research work with an education program. The training will be distributed over the six participating institutions.
 
The successful candidate will work at the Institute for Data, Process, and Knowledge Management under the main supervision of Prof. Axel Polleres. Our institute (cf. https://ai.wu.ac.at) provides a worldwide research network in the area of Graph-based AI, Data and Knowledge Management, where our research provides valuable starting points for each of the three directions outlined above. Moreover, the PhD has is expected to collaborate on a broader level under the co-supervision of another key researcher from the BILAI network, cf. https://www.bilateral-ai.net/consortium/.

What to expect

Proposed Project:
Graph-based structures are highly relevant to all the essential properties of BILAI’s vision of broad and more robust AI. Graph-based structures are inherently symbolic and often equipped with sub-symbolic attributes such as costs or interaction strength. They are omnipresent when solving complex tasks, and can appear as navigation maps, as social or physical interaction networks, or as object relations. Graphs are ideal to transfer knowledge: their nodes and edges represent learned or known abstractions of real-world entities in so-called Knowledge Graphs (cf. for instance, http://kgbook.org); their structure is typically very robust; they can be readily adapted to new situations or even constructed on the fly; they allow for advanced reasoning; and they allow employing efficient algorithms from computer science. Because of the inherent symbolic nature and their suitability for learning and sub-symbolic elements, they naturally constitute a promising starting point as a core component for a bilateral AI approach. 
The proposed PhD project aims to advance the state of the art in this field in working towards
(1)  investigating and understanding the development and evolution of graph structures in real-world (Knowledge) Graphs (KGs) 
(2)  connecting networks of KGs and other structured data corpora, leveraging ML and hybrid AI approaches (incl., for instance, foundation models and RAG), as well as graph modularization and federation techniques
(3)  leveraging both symbolic constraints and graph embeddings and learning approaches to the field of graph data quality improvements & repairs.
 
PhD students will be trained within the Bilateral AI Doctoral School. Joint seminars, scientific workshops, and compulsory courses outside the PhD students’ research fields will also be designed to encourage interdisciplinarity. Apart from that, students will be involved in grant applications, conference organization, Bachelor and Master student supervisions, and teaching. Each student will be supervised by two experienced and internationally renowned professors with different research fields (symbolic / sub-symbolic AI). The training will also provide a career development program, advice and support for students with innovative business ideas, and workshops for presentation and soft skills.

What you have to offer

Applicants for the Ph.D. position must have a master’s degree, which entitles them to enroll for a PhD program, in one of the following subjects: computer science, information systems, business informatics (or a related field of study) with solid practical & theoretical foundations in at least one of the following topic areas:   
  • data science 
  • knowledge representation & reasoning   
  • databases   
  • distributed systems and decentralized computing  
  • semantic web   
  • software engineering   
  • graph theory/graph databases   
We expect excellent study results, technical knowledge of programming languages such as C++, Java or Python, structured data formats such as JSON, XML and RDF, and query languages such as SQL, SPARQL, or graph query languages, etc. as well as proficiency in English. 
 
Do you want to join the Institute for Data, Process and Knowledge Management and the BILAI network? Then please submit your application. The following documents must be submitted (in English) by the call deadline:
 
1.    Letter of motivation (detailing previous research achievements, research goals, career plans);
2.    A complete CV, including a list of previous scientific expertise, awards, grants, stays abroad, attended lectures, attended summer schools, attended workshops, skills, and publications (if applicable);
3.    Abstract in English of the applicant’s MSc thesis, BSc thesis, or of a research project;
4.    A complete list of completed studies and transcripts of all grades;
5.    Two academic recommendation letters;
6.    Proof of proficiency in English (usually TOEFL/IELTS/CAE).
 
By submitting your application, you agree with your application being shared also with members of the BILAI admission committee from other partner universities in the BILAI network.
 
We are looking forward to hearing from you! If you have any questions regarding the position or application documents prior to application, don’t hesitate to contact me for further information at Prof. Axel Polleres axel.polleres[at]wu.ac.at with the subject: "[BILAI Praedoc position]".

What we offer you

  • Inspiring campus life with over 2,400 employees in research, teaching, and administration and approximately 21,500 students
  • A modern campus with spectacular architecture in the heart of Vienna
  • Excellent accessibility by public transportation
  • Meaningful work in an open-minded, inclusive, and family-friendly environment
  • Flexible working hours
  • A wide range of benefits, from an in-house medical officer to athletic activities and a meal allowance to a variety of employee discounts
Curious? Visit our website and find out more at www.wu.ac.at/benefits

The minimum monthly gross salary amounts to €2,684.10 (14 times per year). This salary may be adjusted based on job-related prior work experience. In addition, we offer a wide range of attractive social benefits.

Do you want to join the WU team?
Then please submit your application by December 11, 2024 (ID 2257).
We are looking forward to hearing from you!