July, 5, 2022 BOKU HCAI AI for smart forestry workshop

Our new BOKU Human-Centered AI Lab Vienna Area in beautiful Tulln/Donau, Lower Austria, is taking shape and our mission to connect Lower Austria with Vienna starts: Our first visitors in Lower Austria were from Lower Austria. In our little workshop with colleagues from the University of Applied Sciences St. Pölten we discussed cool topics of digitaltransformation for smart agriculture and forestry, especially some challenges and future aspects of artificial intelligence/machine learning for solving problems in smart forestry, e.g. road trafficability with the help of cyber-physical systems and sensors, or the grand challenge and hot topic of “embodied intelligence”, e.g.: “move to timber – grab the timber – move back to truck” which is easy for humans, but practically impossible for current artificial intelligence – and one solution is in making use of the human-in-the-loop, see our very recent position paper:

Open PhD Positions “Artificial intelligence for smart forest operations”

We are building up our HCAI-Lab in an absolutely cool environment with exciting Artificial Intelligence topics.

Cyber-physical systems, robotics, sensor technology, data management in general, and methods of artificial intelligence (Al) and machine learning (ML) with applications to smart farm and forest operations are of increasing interest.

Work tasks include independent execution and analysis of scientific experiments in Al/machine learning with a focus on smart farm and forest operations, writing scientific publications in a team and presentations as well as lecturing and administrative duties. The completion of a PhD within the position`s timeframe is desired.

Required Skills and qualifications:

  • Master degree in computer science/Informatics
  • Good command of German (spoken) and English (spoken and writing)
  • Proven skills in Python

Desirebable skills and qualifications:

  • Practical experience in conducting experiments in Al/Machine Learning
  • Interest in Cyber-physical systems and embodied intelligence
  • Ability to communicate and work as part of a team

University of Natural Resources and Life Sciences Vienna seeks to increase the number of its female faculty and staff members. Therefore qualified women are strongly encouraged to apply. In case of equal qualification, female candidates will be given preference unless reasons specific to an individual male candidate tilt the balance in his favour.

People with disabilities and appropriate qualifications are specifically encouraged to apply.

Please send your job application incl. motivation letter, your CV, and at least one of your publications in ONE single pdf file,
with the code BY22FAB in the email header (to bypass the automatic spam filter) directly to andreas.holzinger AT human-centered.ai

We regret that we cannot reimburse applicants travel and lodging expenses incurred as part of the selection and hiring process.

Explainable AI Methods – A brief overview (open access)

open access paper available – free to the international research community

AI TechnikerIN gesucht (open position)

Wir suchen für unser junges Forschungsteam ein(e) AI-TechnikerIn mit Abschluss HTL für Informatik Softwaretechnik oder vergleichbarer Ausbildung für die technische Betreuung des Human-Centered AI Labs und Unterstützung unseres jungen Forschungsteams (embodied intelligence, human-in-the-loop robotics, IoT, sensorik, etc) am Institut für Forsttechnik der BOKU Wien am Standort Campus Tulln – 30 Minuten Wien City. Wir bieten ein extrem spannendes Research Environment mit zukunftsträchtigen Entwicklsungsmöglichkeiten. Bei Interesse bitte direkt Kontaktaufnahme via andreas.holzinger AT boku.ac.at

FWF Explainable AI project P 32554 in the News

This basic research project will contribute novel results, algorithms and tools to the international ai and machine learning community

The Next Frontier – AI we can really Trust

Robustness and Explainability are the two ingredients to ensure trustworthy artificial intelligence – talk at ECML 2021

Fairness in Artificial Intelligence Survey

Please take part in our study of Fairness in Artificial Intelligence to help to overcome bias of machine learning