Assistant Professor (non-tenure track)

Candidates with background in data science, information systems, or quantitative methods and models, interested in applying these to climate, environment, or energy systems issues. Interdisciplinary candidates are welcome to apply.

 

What you have to offer

Academic degree and experience (pre-doc position): You have a master’s degree (or equivalent) in any relevant subject area with related to quantitative methods or data science (see below) that qualifies you for enrollment in a doctoral program at WU. You already have an idea for a promising dissertation project.
 
Academic degree and experience (post-doc position): Doctorate or PhD degree in a relevant subject area related to quantitative methods, data science, or energy (see below). You have expertise in the research area proven by the ability (or the potential) to publish in top-tier international academic peer-reviewed journals and participate in acquiring grant funded projects.
 
Relevant research foundations and interests:
  • Academic training involving quantitative methods and/or data science in a variety of disciplines (e.g., data science, information systems, computer science, digital economy, physics, mathematics, economics, applied statistics, operations research, public policy, supply chain management, energy systems, social and economic sciences, engineering)
  • Advanced skills in the following (or related) areas are an additional advantage: databases, large scale data processing, big data management; data science; data ecosystems; machine learning and artificial intelligence (incl information extraction, data mining, natural language processing (NLP), etc.); network science; complex systems
  • Demonstrated interest in energy, climate change, or environmental sustainability through coursework or any relevant experiences on topics including (but not limited to) energy technology innovation or climate-tech (including in electricity, buildings, transport or mobility, and industry), energy policy, industrial policy, energy economics, energy system models, etc.
 
Coding skills: You have advanced knowledge of R, Python or similar programming languages on data science projects
 
Language skills: You have excellent written and spoken English as well as communication skills, knowledge of German (or willingness to learn) is considered a plus
 
Willingness to use multimedia teaching methods: You are prepared to use multimedia teaching and learning formats
 
Working style: You are open-minded, ambitious, have critical thinking skills coupled with interest in working in an interdisciplinary and collaborative team environment. You have strong interpersonal and communication skills and can engage with multiple audiences
 
 
Please submit at least the following documents along with your application:
(a) a motivation letter (2 pages max, highlighting your motivations and qualifications for this position)
(b) a curriculum vitae (including a list of publications (if applicable), and the names and contact information of 2 references from prior employers or academic supervisors)
(c) master or diploma thesis grades and transcripts of your Master and Bachelor studies
(d) a research statement (2 pages max, highlighting any past research experiences and 1-3 future research projects).
 
Please direct any questions to Prof. Kavita Surana at kavita.surana@wu.ac.at

What we offer you

  • Inspiring campus life with over 2,400 employees in research, teaching, and administration and approximately 21,500 students
  • A modern campus with spectacular architecture in the heart of Vienna
  • Excellent accessibility by public transportation
  • Meaningful work in an open-minded, inclusive, and family-friendly environment
  • Flexible working hours
  • A wide range of benefits, from an in-house medical officer to athletic activities and a meal allowance to a variety of employee discounts
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  • Application deadline: Aug 31, 2023
  • Vienna University of Economics and Business
  • Department of Information Systems and Operations Management
  • Vienna, Austria
  • Academic Positions
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