Job Opportunity: PhD Position Data Science / Art History
Please find the application form here: https://jobs.univie.ac.at/job/University-assistant-predoctoral/998213301/
At the University of Vienna, over 10,000 people work together on the big questions of the future. Approximately 7,500 of them are academic staff members. These are individuals who, with their curiosity and their continuous pursuit of excellence, engage in international cutting-edge research and teaching. With us, you will also find space to unfold your potential. We are looking for a
University assistant predoctoral in At History / Data Science Job ID: 1410
Among the many good reasons to want to research and teach at the University of Vienna, there is one in particular, which has convinced around 7,500 academic staff members so far. They see themselves as personalities who need space for their continuous striving and curiosity in order to be able to be scientifically successful. Does that sound like something for you? Welcome to our team!
Your personal sphere of influence:
As a university assistant predoc (75%) – classification according to Collective Bargaining Agreement: §48 VwGr. B1 (predoc) – you will be part of the research team of the Laboratory for Cognitive Research in Art History (https://crea.univie.ac.at/) for three years, from the 1st of January 2024 (or later). You will especially take on tasks in data preparation, analysis, and visualization (Data Science).
The goal of the Laboratory for Cognitive Research in Art History is to advance art historical knowledge through the use of empirical and experimental methods. Projects of the lab deal with classical art historical questions on artworks and their reception as well as transdisciplinary topics in empirical aesthetics and museum studies.
Your future tasks:
You actively participate in research, teaching & administration:
• You will carry out data preparation, analyses, and visualizations in close cooperation with colleagues from the Laboratory for Cognitive Research in Art History.
• You will write a doctoral thesis in cognitive research in art history, digital art history, or transdisciplinary museum studies.
• You will join the Vienna Doctoral School in Cognition, Behaviour, and Neuroscience (VDS CoBeNe, https://vds-cobene.univie.ac.at/).
• You support Prof. Rosenberg in research and teaching.
• You will teach independent courses in the BA Art History curriculum (one course per semester).
This is part of your personality:
• Above average Master's degree in Data Science, Cognitive Science, Art History, Museum Studies, or related discipline,
• advanced knowledge of statistics,
• advanced knowledge of programming languages (especially Python and R),
• knowledge of cluster and network analysis,
• enthusiasm for transdisciplinary research and teamwork,
• independent working and problem-solving skills,
• proficiency in English.
What we offer:
The employment duration is 3 years. Initially limited to 1.5 years, the employment relationship is automatically extended to 3 years if the employer does not terminate it within the first 12 months by submitting a non-extension declaration.
Work-life balance: Our employees enjoy flexible, family-friendly working hours, remote/hybrid and/or part-time work (upon agreement).
Inspiring working atmosphere: You are a part of an international academic team in a healthy and fair working environment.
Good public transport connections: Your workplace in the center of beautiful Vienna is easily accessible by public transport.
Internal further training & Coaching: Opportunity to deepen your skills on an ongoing basis. There are over 600 courses to choose from – free of charge.
Fair salary: The basic salary of EUR 3277,30 (on a full-time basis) increases if we can credit professional experience. Classification according to Collective Bargaining Agreement: §48 VwGr. B1 (predoc).
Equal opportunities for everyone: We look forward to diverse personalities in the team!
It is that easy to apply:
• With your curriculum vitae in tabular form, a letter of motivation, and a list and description of previous data science activities,
• contact details of two personal references,
• copy of Master's certificate (transcript of records), copy of your Master thesis, copies of MA thesis reports (if available),
• via our job portal/ Apply now - button.
If you have any questions, please contact: Hanna Herceg
participants (1)
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Seda Pesen