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Scientific activities / projects, PhD position

Models and procedures for the real-time capable, multimodal acquisition of user and operator states

Starting date

1 September 2020

Duration of contract

3 years


According to the German TVöD 13

Type of employment


"Cutting-edge research requires excellent minds – particularly more females – at all levels. Launch your mission with us and send in your application now!" Prof. Pascale Ehrenfreund - Chair of the DLR Executive Board

The jobholder's task is the development, testing and evaluation of real-time capable models and procedures for the acquisition of relevant cognitive and emotional states of users and operators in traffic-system laboratory and vehicle environments, by means of state-of-the-art machine learning methods and procedures. The basis for the solutions to be developed is formed by the multimodal acquisition and processing of data from (neuro)-physiology (e.g. skin conductance, heart rate, EEG), behaviour (e.g. posture, facial expression, actions, gaze behaviour) and from secondary data sources, such as data on the interaction between man and technology in a systemic context.

To achieve this, the holder of the position will systematically review and analyse the available data, results and developments from previous human-factors projects of the institute, taking into account and assessing the technical effort required to record the individual signal modalities. Based on this, hardware and software requirements for the development of integrated solutions for the discrete, multimodal and synchronised acquisition of user-state data will be formulated under the proviso of an effective and efficient human-factors evaluation of system concepts developed at the institute.

Taking into account the formulated requirements, the developed real-time capable solutions for the acquisition of user and operator states will be further developed, tested and evaluated in order to create robust and high-performance tools for application in laboratory and simulator environments within the framework of the system development and the evaluation of system designs for technical traffic and traffic-system contexts. For this purpose, appropriate scales are to be developed for the recording of selected user states, and limit values are to be determined and validated which are critical for relevant criteria (e.g. safety, user acceptance, trust) within the framework of system evaluation.

Your qualifications:

  • a completed scientific university degree in cognitive science, computer science or data science
  • knowledge of machine learning methods
  • programming knowledge in Python, in particular with machine learning libraries, such as Tensor Flow or Keras
  • experience in the planning, design, testing and evaluation of machine learning applications
  • sound knowledge of the acquisition, validation, fusion, analysis and evaluation of data from different data sources
  • experience in conducting research projects and empirical studies
  • experience in data analysis with scripting languages such as R or Python
  • experience in working with interdisciplinary teams, ability to work in a team
  • very good English, both written and spoken
  • sound knowledge in the development and evaluation of machine learning applications is an advantage
  • sound knowledge of programming with scripting languages such as Python or Matlab is a plus
  • ideally scientific publications and presentations at specialised national and international conferences
  • experience in the acquisition, pre-processing and evaluation of physiological data is advantageous
  • experience in the development of machine learning applications for user-state or user-activity classification is desirable
  • knowledge in the field of software engineering is beneficial
  • interest in topics of human-machine interaction, particularly within the transport system
  • interest in topics of emotion psychology

Your benefits:

Look forward to a fulfilling job with an employer who appreciates your commitment and supports your personal and professional development. Our unique infrastructure offers you a working environment in which you have unparalled scope to develop your creative ideas and accomplish your professional objectives. Our human resources policy places great value on a healthy family and work-life-balance as well as equal opportunities for persons of all genders (m/f/non-binary). Individuals with disabilities will be given preferential consideration in the event their qualifications are equivalent to those of other candidates.

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Technical contact

Uwe Drewitz
Institute of Transportation Systems

Phone: +49 531 295-3121

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Vacancy 49686

HR department Braunschweig

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DLR site Braunschweig

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DLR Institute of Transportation Systems

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