Senior Scientist at the Research Platform Cognitive Science

The University of Vienna (19 faculties and centres, 178 fields of study, approx. 9.600 members of staff, about 92.000 students) seeks to fill the position from 01.03.2019 of a


Reference number: 9114

The new founded Vienna CogSci Hub at University Vienna serves as a focal point for the future growth of Cognitive Science and Cognitive Neuroscience. The Vienna CogSci Hub integrates and provides access for its members to a multi-disciplinary Cognitive Science Methods Unit (CogSci Labs), including our existing neuroimaging center (fMRI), eye tracking, brain stimulation, NIRS, behavioral physiology and virtual reality (all based on existing equipment provided by the CogSci members).



Duration of employment: 3 year/s

Extent of Employment: 40.0 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.

Job Description:
We are looking for a Statistician or Data Scientist with experience in statistical analysis, computer programming and preferably contemporary machine learning methods (e.g. Deep Network Models) and computational modeling. This includes researchers in one of the disciplines related to Cognitive Science with a specialization in this area. The ideal candidate would have a PhD in a Data Science field (e.g. applied mathematics or statistics, informatics), but also a strong interest (and preferably experience) in developing and applying computational models as well as in analyzing data from Cognitive (Neuro) Science methods, such as fMRI, EEG, eye tracking, virtual reality or cognitive modeling.
This individual would assist CogSci researchers in performing sophisticated and multivariate data analyses and generating state-of-the-art data visualizations.

Responsibilities for Data Scientist
• Mine and analyze, visualize and interpret complex scientific data from experiments and field studies
• Assess the effectiveness and accuracy of new data sources and data gathering techniques.
• Develop custom scientific data models and algorithms to apply to data sets.
• Work with researchers from various disciplines to develop interdisciplinary innovative research designs, collaborate in writing national and international research grant applications.
• Cooperate and network with diverse research groups in Vienna University regarding data mining, modeling, etc.
• Develop and hold workshops with scientists

Profile:
PhD in Data Science, Mathematics, Statistics, Computer Science or the like - 1-3 years practice in scientific data analysis in Cognitive Science, Psychology, Biology or other disciplines related to Cognitive Science - Strong problem solving skills in a scientific environment. - Excellent written and verbal communication skills for coordinating across teams. - A drive to learn and master new technologies and techniques. - Experience using statistical computer languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets. - Experience with Matlab - Experience working with and creating data architectures. - Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications. - Experience in visualizing/presenting data for stakeholders using for example tools like Periscope, Business Objects, D3, ggplot, etc.
We ask for a minimum of one letter of recommendation.

Candidates are asked to forward the tools they have worked with and their level of expertise therewith. Examples are: - Coding knowledge and experience with several languages: R, Python, Java, JavaScript, etc. - Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc. - Experience querying databases and using statistical computer languages: R, Python, SQL, etc. - Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc. - Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks. - Experience with scientific computing - Experience in cooperation with in house IT-services


Research fields:

Main research field	Special research fields	Importance
Mathematics	Statistics;Analysis	CAN

Education:

Educational institution	Educational level	Special subject	Importance
University	Mathematics, Computer Sciences	-	SHOULD

Languages:

Language	Language level	Importance
English	Excellent knowledge	MUST
German	Good knowledge	CAN

Computer-Skills:

Type of computer skills	Specified computer skills	Importance
Programming language	Others	CAN

Applications including a letter of motivation (German or English) should be submitted via the Job Center to the University of Vienna ( http://jobcenter.univie.ac.at) no later than 08.02.2019, mentioning reference number 9114.

For further information please contact Spee, Blanca Thea Maria +43-1-4277-22002.

The University pursues a non-discriminatory employment policy and values equal opportunities, as well as diversity ( http://diversity.univie.ac.at/). The University lays special emphasis on increasing the number of women in senior and in academic positions. Given equal qualifications, preference will be given to female applicants.

Human Resources and Gender Equality of the University of Vienna
Reference number: 9114
E-Mail: jobcenter@univie.ac.at
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