Professorship in Quantitative Methods (full-time or part-time)

Contenido de trabajo

About XU

The XU Exponential University of Applied Sciences is a private, state-accredited university of applied sciences in Potsdam, Brandenburg. XU’s offerings are consistently geared towards the digital transformation, the start-up fast-growing digital entrepreneurial innovation and the new competencies and skills for the jobs of the future.

XU’s goal is to enable students, entrepreneurs, employees and managers to grow in the digital age and actively shape the digital transformation. We are looking for professors (m/f/d) for our study programs who represent digitalization topics, who hold entrepreneurial, innovative and international mindset in teaching and research and who are enthusiastic about building a new university of applied sciences focused on Industrial Revolution 4.0 challenges.

As we are growing exponentially, we are looking for enthusiastic candidates (m/f/d) to join our team as soon as possible in the role of Professor (m/f/d) for Quantitative Methods. Applications for this new post are invited from outstanding candidates in the field of quantitative methods, with a focus on nature and social sciences, namely data science and digital business aspects.

Tasks

• Teaching courses of quantitative methods, mathematics, statistics and related subject areas in the context of digital business, data science and artificial intelligence in our (current) Data Science, Digital Business, Digital Marketing, Coding and Software Engineering bachelor and (planned) Digital Transformation master programs (in addition, teaching courses in the field of data science and artificial related topics, though not a mandatory requirement is considered a plus).
• Supervising examinations, internships, projects, bachelor and master theses.
• Participating in the further development, consultation and organization of new courses.
• Planning and implementation of research and development projects, including publishing activities and other initiatives as adequate.
• Establishing a network with partner companies and supporting internships and collaborative projects.
• Participating in the academic self-administration of the university.
• Self-identification with the innovative teaching approach of the XU Exponential University.
• Commitment to contribute to the teaching experience with an interdisciplinary approach, as well as with practical experience in a digitally growing world. Experience with start-ups as well as with the associated environment are desirable.
• Commitment to engage and develop further the XU innovative and interactive didactic concepts and methods. Commitment to participation in interdisciplinary courses as well as in the implementation of English-language courses.
  

Requirements

• Completed doctoral or PhD studies in the field of Mathematics, Statistics, Computer Science, or other related subject area.
• Pedagogic and didactic experience for academic teaching in English.
• Practical professional experience of quantitative methods in the industry of at least 5 years (preferably after completing the PhD), with a focus on data science or relevant sub-specialization subject areas, e.g., artificial intelligence, or computational statistics fields is considered a plus.
• Research track record in the quantitative methods field proven by consultancy projects and/or publications in international scientific conferences and journals, etc. Additional experience in the acquisition, execution and management of research projects is a plus.
• Knowledge and experience of undertaking research on quantitative methods, preferably with an intersectional focus on data science, and/or computational, artificial intelligence, computational statistics aspects.
• Experience with at least some of the latest trends in quantitative methods, preferably when related data science and digital business application fields.
• It is expected that the future holder of the position will shift his/her center of life to Berlin/Potsdam area (on-site presence).
• Very good communication skills and teamwork, ability to interact and motivate students and other key stakeholders.
• Fulfill the official requirement captured by
• 41 of State of Brandenburg (Brandenburgisches Hochschulgesetz (BbgHG)).
  

Which other criteria are important?

• Relevant teaching experience in quantitative methods.
• Additional teaching in the field of computer science and IT related topics, though is not mandatory, is considered a plus.
• Relevant experience in the supervision of scientific work of students, such as bachelor and master theses is desirable.
• Broad professional practical experience (with leadership responsibility) in the field of the appointment, for example in tech start-ups, tech companies, industry and/or in consulting related to data science, complete your profile.
• Core values and social commitment to XU community and beyond matter, of course, for us.
• In addition, we would like to see your enthusiasm and active involvement in building a new university and interest in producing an impact beyond.
• Teaching experience in German, though not mandatory is considered a plus.
• International experience, both industrial and academic.
• Entrepreneurial mindset.
  

Benefits

• Excellent working conditions in an attractive modern environment
• The opportunity to impact on a young university.
• The chance to set your own focus in research, as well as in new courses of study and, in the future, new subject areas, etc.
• Friendly atmosphere, teamwork-oriented and committed colleagues who love what they do.
• The opportunity to build and develop processes that ensure high-quality teaching and innovative research in the long term.
  

Sounds interesting?

Then we look forward to receiving your complete digital application. Please submit your documents via email only. Applications are currently being considered.

Application

Please, include the following information

in your application and submit your application in a single PDF file.

• Cover letter explaining your motivation to join XU.
• Detailed resume and list of publications.
• Doctoral certificate.
• University certificates.
• An overview of the courses and projects you have held so far (scope, subject).
• Relevant experience certificates.
• Teaching experience including evaluation forms (if available).
• Teaching statement describing potential courses to cover.
• Research statement describing your research vision.