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Predicting attitudes and behavior concerning living materials: Develop software and analyses methods to apply cognitive affective maps

Doctoral position in the Area of Psychology

Evaluations and behavioral decisions constitute essential, complex cognitive and affective psychological processes with many determining factors. Consequently, we expect a multitude of factors to have an impact on the acceptance of living materials systems. We will apply multi-method approaches to develop and validate computational models predicting acceptance of living materials systems. Our focus is on the development of new approaches to acceptance research, especially towards the prediction of acceptance of technical systems which do not exist yet. In this project, we aim to advance “Cognitive Affective Maps” (CAMs), a novel approach to predict acceptance based on cognitive and affective factors. In detail, we will first create a suitable software package in order to use CAMs for data collection. Second, we will scrutinize different ways for data aggregation of large samples of participants and we will implement these options in the software package. Third, we will validate CAMs assessing a coherent cohort (students). The projects entails preparation, implementation and evaluation of experimental studies as well as the development, construction, and evaluation of computerized models.

Expected candidate profile:
  • Degree in Psychology, Computer Sciences or Cognitive Sciences (diploma / master).
  • Good skills in methods and statistics.
  • Very good social, organizational and communication skills.
  • Ability to work both independently as well as in a team.
  • Willingness and interest to tread new conceptual and methodological ground in interdisciplinary cooperation with other projects within the cluster of excellence.
  • Very good English skills.
  • Programming skills, especially for the development of computer models, e.g. artificial neural networks, would be an asset
 
Further information and details with regard to the application process can be found here. We expect to fill this position by April 1st 2019.The position will be supervised by Prof. Dr. Andrea Kiesel.
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