Host institution: TU Dublin Duration: 36 Months
Objectives: Build a holist model for human performance real time assessment and gather and test the data necessary to validate hypothesis in relation to for real time prediction of Human-machine interaction performance (predicting cognitive load, fatigue and other human factors state connected with a scenario and the likelihood of error given them) on the basis of the data of the three live labs. The Model will be built using a AI method (e.g. BBN)
The candidate should preferably have the following skills:
- Master’s degree in industrial engineering or other related subject, computer science, artificial intelligence, mathematics or related field of study
- Knowledge of probabilistic graphical models will be considered an advantage
- Knowledge of Human Factors is also considered an advantage
- Ambitious in research and problem solving
- Good communication skills in English (both in writing and orally)
- Strong motivation to work in a small team and individually
Expected Results:
Building the innovative methodological framework and tools for the effective exploitation of integrated field data (technical and HOF) for sustainability
Defining sustainability performance indicators and the field data need to assess them
Acquiring the knowledge on the use of AI algorithm to be deployed (BBN)
Validate the knowledge acquired and the approaches devised on real case study applications
Planned secondment(s): The PhD student is going to be seconded on M 12 in mBrainTrain for 9 months to learn about Neuroergonomics tools and data collection / interpretation methods,in DIGITALSME at M21 for 3 months to receive the legal and ethical trainingand be exposed to best practices form selected SMEs of the alliance and in Yokogawa at M24 for 6 months to work on the case stud on HMI for LIVE LAB3.
to access the application form click on this link: Application form