Senior Scientist

vor 3 Wochen

Wien, Österreich Universität Wien Vollzeit

The University of Vienna (20 faculties and centres, 184 fields of study, approx. 10.400 members of staff, about 90.000 students) seeks to fill the position as soon as possible of a

**Senior Scientist**

**at**
**the**
**Department of Cognition, Emotion, and Methods in Psychology**

**Reference number***:
**13936**

The Faculty of Psychology consists of the Dean’s office and the studies service center, as well as - Department of Cognition, Emotion, and Methods, - Department of Occupational, Economic and Social Psychology, - the Department of Applied Psychology: Work, Education and Economy, - Department of Developmental and Educational Psychology - the Outpatient Unit for Research, Teaching and Practice. Currently, nearly 3,500 students of Psychology are enrolled in Bachelor's, Master's and PhD programmes, attending nearly 200 courses per semester, which are taught and supervised by 220 teachers.

**Extent of Employment**: 40 hours/week

Job grading in accordance with collective bargaining agreement: -48 VwGr. B1 lit. b (postdoc) with relevant work experience determining the assignment to a particular salary grade.

Applicants should have a strong interest in machine learning methods applied to psychological and clinical data. This includes excellent knowledgde of interpretable machine learning tools and experience in data management (DSGVO). They should also be experienced in teaching machine learning methods to psychology students through lectures and hands-on practical training, including supervision of psychology Theses and internship projects in this field. Further, applicants should also have a solid background in neurotechnologies, including brain-computer interfaces based on real-time neuroimaging and physiological signals. This includes online signal processing of fMRI, EEG, simultaneous EEG-fMRI, EMG, EOG, EDA, ECG, HR, respiration as well as eye tracking data, and their multimodal integration via LabStreamingLayer. Experience with joint Tech-University research projects and grants as well as with SCRUM workflow management is an advantage. Applicants should also demonstrate successful contributions of machine learning and neurotechnology methods to support third-party funding initiatives.

Applicants should have one of the following profiles: A degree in Biomedical Engineering and/or Computer Science, with solid experience in machine learning and neurotechnologies. Applicants should send their CV, a brief statement of research interests, and the names and contact information for 2 references. Participation in teaching and independent teaching of courses as defined by the collective agreement.

**Profile**:
The following skills and activities are considered a plus: ability to work in a team; autonomous and proactive working style; evidence of independent research as a senior author; experience as a reviewer and editor; outreach activities; Python (e.g, scikit-learn, scikit-optimize, matplotlib, lightgbm, xgboost, shap, scipy, pandas); Matlab (e.g. SPM); experience with real-time neuroimaging and physiological signals (online signal processing, fMRI, EEG, simultaneous EEG-fMRI, EMG, EOG, EDA, ECG, HR, respiration, eye tracking); LabStreamingLayer; experience with joint Tech-University research projects and grants; SCRUM experience (e.g. certified SCRUM Master); experience in computer infrastructure administration, data storage, management and sharing; DSGVO training.

**Research fields**:
**Main research field**

**Special research fields**

**Importance**
- Medical Engineering- Biomedical engineering- SHOULD**Education**:
**Educational institution**

***

**Educational level**

**Importance**
- University- Electrical Engineering, Electronics- Electro
- an biomedical technology- SHOULD- University- Mathematics, Computer Sciences- Informatics- SHOULD**Languages**:
**Language**

***

**Language level**

**Importance**
- German- Very good knowledge- MUST- English- Very good knowledge- MUST**Computer-Skills**:
**Type of computer skills**

**Specified computer skills**

**Importance**
- Programming language- Others- CAN- Basic Knowledge- Others- CAN- Basic Knowledge- Others- CANFor further information please contact Scharnowski, Frank +43-1-4277-47120.

**Reference number: 13936

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