We are hiring: PhD student Machine Learning

Machine Learning for Data Management

You will identify, develop and test machine learning use cases that improve data quality. You will be employed with HEC Lausanne and work in the Competence Center Corporate Data Quality (CC CDQ), an industry-funded research consortium. In your research, you will closely collaborate with an industry partner in the sports industry on identifying and implementing ML use cases that advance data management. Starting date is negotiable as from June 2019 to October 2019.

Desired qualifications:

  • Master's degree in Information Systems, Computer Science or related field
  • Strong interest in one or more of the following topics: machine learning, data science, advanced analytics, data curation, data management, business information systems
  • Relevant internships and/or practical experience (e.g. as a developer or consultant)
  • Excellent analytical and communication skills
  • Good writing skills and fluency in English; German and/or French are a plus

Employment rate is 100% with a competitive salary and a maximum contract duration of five years. Starting date is negotiable as from January 2019. The PhD candidate is expected to enrol in the doctoral school in information systems at HEC Lausanne and will be supervised by Prof. Christine Legner.

HEC Lausanne is one of the leading European business schools. The school received the AMBA and EQUIS accreditations for the overall quality of its programs, research, and teaching. It is situated at the shores of the lake of Geneva in one of the most beautiful places in Switzerland. An excellent public transport network links the university campus in just a few minutes to Lausanne, the capital of Vaud, noted for its varied cultural activities.

Informal inquiries and how to apply

For any inquiry about the PhD positions, please contact Prof. Christine Legner:
christine.legner@unil.ch or +41 21 692 3432.

Please submit your Curriculum Vitae, university transcripts (bachelor and master level) and an electronic version of a recent research project (e.g. master thesis, scientific publication) by e-mail.

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